genetic control of apigenin di-c-glycoside biosynthesis in ......chapter v: contribution of apigenin...
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Genetic control of Apigenin di-C-glycoside
biosynthesis in bread wheat grain and their role
as yellow pigments of Asian alkaline noodles
Submitted by
Grace Yasmein Wijaya
This thesis is submitted to Faculty of Sciences in fulfilment of the
requirements for the degree Doctor of Philosophy
Faculty of Science
The University of Adelaide
November 2012
This book is An Answer to Prayers of a Long list of Believers
I have been very blessed and loved with all of your spiritual supports, for His guidance and
protections, and sincerely will not have enough to thank you all.....
May you all be blessed and loved, too
As I have been always,
yasmein
i
Table of Content
Table of Content i
List of Tables x
List of Figures xiii
List of Supplemental Materials xxv
Summary xxx
Statement of Authorship xxxiv
List of Publications xxxv
Acknowledgement xxxvi
List of Abbreviations xxxix
Chapter I: General Introduction 1
1.1 Background 1
1.2 Knowledge Gap 2
1.3 Structure of thesis 2
Chapter II: Literature review 4
2.1 Asian noodles as one of the major end-products of Australian bread wheat 4
2.2 Yellow colour of YAN 5
2.2.1 Natural Compounds that contribute to the yellow colour of YAN 5
2.2.1.1 Types of natural compounds that contributes to the yellow colour of YAN and
their roles in plants and human health 5
2.2.1.2 Contribution of xanthophylls and ACGs to the yellow colour of alkaline noodles
8
2.2.2 Factors influencing the measurement of the yellowness of noodles and the content
of xanthophyll and ACG in wheat grain 10
ii
2.2.3 The amount, tissue location and composition of xanthophylls and apigenin di-C-
glycosides in wheat grain and recovery in flour following milling 11
2.3 Apigenin di-C-glycoside biosynthesis in plants 12
2.3.1 Flavonoid biosynthetic pathway 12
2.3.2 Pathway leading to apigenin di-C-glycoside biosynthesis in wheat grain 15
2.3.3 UDP-sugar recognition by the glycosyltransferases 20
2.4 Genetic regulation of flavone biosynthesis in cereal grain 21
2.4.1 Genetic loci involved in the control of compounds related to the yellow colour of
alkaline noodles 21
2.4.2 Transcriptional regulation of flavonoid biosynthesis 23
2.4.3 Transcription factors controlling flavonoid biosynthesis in cereal grain 24
2.5 Wheat genomics for studying genetic regulation of flavone-di-C-glycoside
biosynthesis 27
2.5.1 Organization of the wheat genome and wheat genomic information 27
2.5.2 Methods for studying regulation of gene expression in wheat 30
2.5.2.1 Reverse and forward genetic approaches for studying regulation of gene
expression in wheat 30
2.5.2.2 Identification of transcription factor genes through genetic mapping and
positional cloning 31
2.5.2.3 Availability of resources for synteny analysis to determine transcription factor
gene sequences 33
2.5.2.4 Transcript analysis of wheat genes 36
2.6 Conclusion 37
2.7 Research questions 38
2.8 Research aims 38
iii
2.9 Significance/contribution to the discipline 39
Chapter III: General Materials and Methods 40
3.1 Introduction 40
3.2 Plant Materials 40
3.2.1 Genetic resources for experiment 1 (Chapter IV): Survey of genetic variation in
ACG content and composition 40
3.2.2 Genetic resources for experiment 2 (Chapter V): Quantitative assessment of
content and composition of the ACGs and their contribution to YAN colour in
comparison to that of lutein 41
3.2.3 Population for experiment 3 (Chapter VI): Genetic control of the ACG content
and composition in bread wheat grain 42
3.2.3.1 Parents of Australian doubled haploid populations 42
3.2.3.2 Sunco/Tasman doubled haploid population used in the QTL mapping 42
3.2.3.3 Other genetic stocks used in marker analysis 44
3.3 Location, time, and condition of planting of the genetic resources 45
3.4 Phenotyping 46
3.4.1 Data collection 46
3.4.1.1 ACG analysis 46
3.4.1.2 The Use of Internal and external standard solutions in ACG Analyses 47
3.4.1.2.1 The use of vanillin internal standard in ACG analyses 47
3.4.1.2.2 The used of rutin internal standard 48
3.4.1.2.3 The use of rutin external standard 48
3.4.1.3 Hundred grain weight 48
3.4.2 Data Analysis 49
3.4.2.1 Calculations of ACG traits 49
iv
3.4.2.2 Statistical Analysis 50
Chapter IV: Apigenin di-C-glycosides (ACG) content and composition in grains of
bread wheat (Triticum aestivum L.) and related species 53
4.1 Introduction 53
4.2 Material and Methods 54
4.2.1 Plant materials 54
4.2.2 Apigenin di-C-glycoside analysis 56
4.2.3 Experimental design and data analysis 56
4.3 Results and discussion 57
4.3.1 Apigenin di-C-diglycoside analysis 57
4.3.2 Apigenin di-C-glycoside concentration and content per grain 58
4.3.2.1 ACG concentration 58
4.3.2.2 ACG content per grain 60
4.3.2.3 ACG content of reciprocal F1 and parental grain 64
4.3.2.4 ACG content of nullisomic-tetrasomic lines of Chinese Spring and Chinese
Spring/Triticum spelta chromosome substitution lines 66
4.3.2.5 Relative effects of genotype and environment on ACG content 66
4.3.3 Apigenin di-C-glycoside composition, ACG1/ACG2 67
4.3.3.1 ACG composition and pedigree of Triticum aestivum L. cultivars 68
4.3.3.2 ACG1/ACG2 ratio in reciprocal F1 grains and their parents 69
4.3.3.3 ACG composition of nullisomic-tetrasomic lines of Chinese Spring 69
4.3.3.4 Correlation among ACG components 71
4.4 Conclusions 72
Chapter V: Contribution of Apigenin di-C-glycoside (ACG) to the colour of yellow
alkaline noodles (YAN) in comparison to that of Lutein 77
v
5.1 Introduction 77
5.2 Materials and Methods 79
5.2.1 Plant materials 79
5.2.2 Preparation of flour and noodles 80
5.2.2.1 Grain milling 80
5.2.2.2 Preparation of noodle sheets 81
5.2.3 Measurement of colour of YAN and WSN 82
5.2.4 Analyses of yellow pigment content in grain and flour 83
5.2.4.1 ACG analysis of grain and flour 83
5.2.4.2 Lutein analysis of grain and flour 84
5.2.4.2.1 Lutein extraction and analyses 84
5.2.4.2.2 The use of internal and external standard solutions in lutein analyses 85
The use of -apo-8’-carotenal as internal standard 85
The use of xanthophylls to construct the standard curves 86
5.2.5 Estimation of ACG contribution to yellowness of YAN 86
5.2.6 Data analysis 87
5.3 Results and Discussion 88
5.3.1 ACG and lutein content in wheat grain and flour 88
5.3.1.1 The effect of milling on the proportion of ACG and lutein in relation to their
tissue location in the grains 87
5.3.1.2 Comparison of Bühler and Quadrumat Junior Mills 92
5.3.1.3 The influence of grain physical properties on milling 93
5.3.2 Yellowness of YAN and its correlation with lutein and ACG concentration 97
5.3.3 Yellow colour developed in the presence of alkaline salts 98
5.3.4 Prediction of the contribution of ACG to b* (YAN-WSN) 102
vi
5.3.5 Contribution of ACG to b*(YAN –WSN) 103
5.4 Conclusions 105
Chapter VI: QTL associated with Apigenin di-C-glycoside (ACG) concentration and
composition in bread wheat (Triticum aestivum L.) grain and identification of candidate
genes 111
6.1 Introduction 111
6.2 Material and methods 113
6.2.1 Plant material 113
6.2.2 Validation of the QTL associated with variation in ACG composition, ACG
concentration, and 100 grain weight in the Sunco/Tasman 114
6.2.2.1 Construction of new genetic maps for Sunco/Tasman incorporating additional
markers 114
6.2.2.2 QTL analyses of ACG concentration, ACG composition and 100 grain weight.
115
6.2.3 Addition of markers to the major QTL for ACG concentration and composition
located on 7BS 116
6.2.3.1 DNA Isolation 116
6.2.3.2 SSR marker analysis 117
Polymorphism test 117
Mapping polymorphic markers in the Sunco/Tasman doubled haploid population 118
6.2.3.3 Single nucleotide polymorphism (SNP) marker analysis 119
Source of SNPs 119
SNP marker analysis 119
6.2.3.4 Apigenin-C-diglycoside analysis 122
6.2.3.5 Linkage mapping and QTL analysis 122
vii
Comparison of 7BS of Sunco/Tasman with other wheat maps 123
6.2.4 Synteny between wheat, rice and Brachypodium distachyon 123
6.2.4.1 Wheat 7BS and rice chromosomes 6 and 8 123
6.2.4.2 Wheat and Brachypodium distachyon 124
6.2.5 Multiple alignment and structural analysis of candidate sequences 124
6.3 Results and discussion 125
6.3.1 ACG content and composition of Sunco/Tasman parents and doubled haploid
population 125
6.3.2 QTL for ACG content and composition in Sunco/Tasman 128
6.3.3 Fine mapping of ACG QTL on 7BS of Sunco/Tasman 132
6.3.3.1 Additional markers 132
6.3.3.2 The order of SSR markers within the QTL on 7BS of Sunco/Tasman compared
with other populations and a consensus map 135
6.3.3.3 QTL for the ACG traits 135
6.3.4 Synteny between the wheat 7BS chromosome region harbouring the QTL
associated with variation in ACG traits with the physical maps of rice and
Brachypodium distachyon 141
6.3.4.1 Synteny with rice chromosomes 6 and 8 141
6.3.4.2 Synteny with Brachypodium distachyon chromosomes 1 and 3 147
6.3.5 Candidate genes related to variation in ACG biosynthesis in wheat 151
6.3.5.1 The glycosyltransferases 151
6.3.5.2 Other candidate genes for the major and minor QTL associated with ACG
content and composition. 156
6.4 Conclusion 157
viii
Chapter VII: Identification of SNPs and haplotypes in candidate genes for Apigenin di-
C-glycoside (ACG) biosynthesis in bread wheat (Triticum aestivum L.) grain: flavanone
2-hydroxylase (F2H) and C-glycosyltransferase (CGT) 160
7.1 Introduction 160
7.2 Materials and Methods 161
7.2.1 Plant Materials 161
7.2.1.1 gDNA 161
7.2.1.2 mRNA 162
7.2.1.3 cDNA synthesis 162
7.2.2 Degenerate primer design to amplify F2H and CGT sequences in bread wheat
163
7.2.2.1 Source of CGT and F2H sequences 163
7.2.2.2 Sequence alignments 163
7.2.2.3 Primer design 164
Primer pairs for amplification of the CGT 164
Primer pairs for amplification of the F2H 164
7.2.3 Amplification of CGT sequence from wheat gDNA and cDNA by the degenerate
primer pairs 169
7.2.3.1 Optimization of PCR 169
7.2.3.2 Isolation and purification of prospective CGT DNA bands 170
7.2.3.3 Cloning and sequencing of prospective CGT DNA bands 171
Cloning of prospective DNA bands in pDrive cloning vector 171
Transformation of p-Drive recombinant plasmid into Escherichia coli 171
DNA Plasmid isolation and purification 172
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7.2.4 Amplification of CGT sequence from wheat gDNA and cDNA by nested PCR
173
7.2.5 Optimation of PCR for re-amplification of EcoRI restriction product 173
7.3 Results and Discussion 174
7.3.1 Isolation, purification and cloning of CGT candidate genes for ACG ratio 174
7.3.1.1 PCR optimization 174
PCR with gDNA 174
PCR using a cDNA template 175
Re-amplification of PCR products of CGTF3R2 primer pair with cDNA template from
Sunco and Tasman embryo 178
7.3.1.4 Sequences obtained from the amplification 178
7.3.2 Proposed Future work 184
7.3.2.1 Identification of more Wheat EST sequences 184
7.3.5.2 Putative function of the wheat EST sequences 184
7.3.5.3 Rapid amplification cDNA ends (RACE)-PCR or chromosome/subgenome
walking to obtain the full sequence of CGT from wheat ESTs 188
RACE-PCR (Life TechnologyTM Protocol-Invitogen) 188
Chromosome/subgenome walking 188
7.4 Conclusion 189
Chapter VIII: General Discussion 191
8.1 Proposed genetic control of ACG biosynthesis in bread wheat grain 191
8.2 Implication of the proposed genetic control for future study and application of the
ACGs 194
Supplemental materials 196
Bibliography 239
x
List of Tables
Table 2.1 Types of noodles based on nature of raw materials used, pH and organoleptic
qualities (Corke & Bhattacharya 1999). 4
Table 2.2 Enzymes involved in flavone biosynthesis. 16
Table 2.3 DNA markers on chromosome 7B that were linked with ratio, ACG1/ACG2
in grain of Sunco x Tasman population (Mares and Wilsmore, unpublished
data). 22
Table 2.4 Online Resources for comparative genomic study of plants. 29
Table 3.1 Locations and time of planting of the genetic resources used in this thesis.
45
Table 4.1 Range and means (+ SE) for apigenin di-C-glycoside (ACG) content in grain
of diploid, tetraploid, and hexaploid wheat species. The concentration and
content are presented as the concentration (g/g) and content in the grain
(g/grain) of each type of ACG (ACG1 and ACG2) and total ACG. The
ACG1, ACG2, and total ACG data for all lines are available as
supplementary file 1. 62
Table 4.2 Means (+ SE) for 100 grain weight of the diploid, tetraploid, and hexaploid
wheat. a-i: indicate significant differences (p<0.01) in 100 grain weight based
on Duncan test of multiple comparison at 5% level. 63
Table 4.3 Concentration, proportion and composition of the Apigenin di-C-glycosides
(ACGs) in de-embryonated grain and embryo of F1 reciprocal cross of
Sunco-Tasman and Gamut-Reeves parent pairs. 65
Table 5.1 Total ACG and lutein concentrations in grain and flour and the percentage
recovery in Quadrumat Junior mill flour. 91
xi
Table 5.2 Proportion of total yellow pigments in flour compared with grain; range and
means for 28 bread wheat cultivars. The ACGs are presented as ACG1 and
ACG2 while the luteins are presented as lutein, lutein-monoester, lutein-
diester and total lutein-ester. 92
Table 5.3 Yellow colour (b*) of YAN and WSN made from Quadrumat Junior Mill
flour and the portion of YAN b* and b*(YAN b*-WSN b*) developed in
the presence of alkaline salt, for 28 bread wheat cultivars at 0, 2, 4 and 24
hour. 99
Table 5.4 Correlation between total lutein content, ACG content, recovery of grain
lutein or ACG in flour with YAN b* and b* (YAN b*-WSN b*). # signifies
the significant correlations. 100
Table 5.5 The predicted values for b* of YAN sheets made from grain of 28 cultivars
of bread wheat milled by Quadrumat Junior Mill, based on rutin-b* standard
curve (Figure 5.2). 105
Table 6.1 Wheat EST sequences from chromosome 7B of wheat with homologous
sequences in rice (chromosome 6 and 8) and Brachypodium distachyon
(chromosome 1and 3) and their genome specific primer (GSP) sequences
(Wheat SNP database, USDA). 121
Table 6.2 QTL associated with ACG traits in Sunco/Tasman doubled haploid
population. The QTL were backward selected from the genome scan with
CIM. All of these QTL are significant at LOD threshold = 3.405, except *.
131
Table 6.3 QTL on 7BS of Sunco/Tasman after additional SSR markers were added.
139
xii
Table 6.4 QTL and QTL effect for ACG1/ACG2 ratio analysed as a binary trait A/B
(Data output from GENSTAT 14 QTL Analysis, Single Trait Linkage
Analysis (Single Environment). 139
Table 7.1 Degenerate Primers to amplify CGT in bread wheat 169
Table 7.2 Degenerate Primers to amplify F2H sequences in bread wheat 169
Table 7.3 Results of megablastn into nucleotide collection. DNA sequences (figure 7.4)
were used as query sequences. 183
Table 7.4 Information on the wheat ESTs that were used to design primers for targeting
CGT sequence(s) in bread wheat. 185
Table 7.5 Similarity between wheat ESTs that were used to design primers for targeting
CGT sequence(s) in bread wheat and rice CGTs. 185
xiii
List of Figures
Figure 2.1 Structure of lutein (all-trans Lutein) (Abdel-Aal et al. 2007). 6
Figure 2.2 The general structure of flavones. ACGs are identified by sugar groups
attached to 8-C and 6-C (Asenstorfer et al. 2006). 8
Figure 2.3 Anatomy of wheat grain tissues (Anon 1960). Embryo, endosperm and grain
coat tissues comprise 2-3%, 81-84% and 14-16% of the grain respectively.
9
Figure 2.4 The flavonoid metabolic pathway (Asenstorfer et al. 2007, Ayabe & Akashi
2006, Cummins et al. 2006, Lepiniec et al. 2006, Martens & Forkmann 1999,
Shirley 2001). The colours indicate branches of the pathway that lead to
production of different types of flavonoid compounds. Enzymes that catalyse
specific parts of the pathway are shown in blue. Those that function in the
first part of the flavonoid pathway: CHS (chalcone synthase) and CHI
(chalcone isomerase). Those are proposed to function in flavone di-C-
diglycoside biosynthesis: F2H (2S-flavanone 2-hydroxylase) and FCGT
(flavonoid C-glycosyltranferase), while those that function in flavone
biosynthesis: FS1 (flavone synthase 1) and FS2 (flavone synthase 2). Other
branches leading to anthocyanin biosynthesis: F3H (flavanone-3β-
hydroxylase), DFR (dihydroflavonol-4-reductase), ANS (anthocyanidin
synthase), UFGT (UDP glycose:flavonoid-3-O-glycosyltransferase), for
flavonol biosynthesis: FLS (flavonol synthase); RT (rhamnosyl transferase),
for aurones biosynthesis: AS (aureusidin synthase), for isoflavones
biosynthesis: IFS (isoflavones synthase), for proanthocyanidin biosynthesis:
xiv
LAR (leucoanthocyanidin reductase) and ANR anthocyanidin reductase.
14
Figure 2.5 Proposed biosynthesis pathway for the 2 types of apigenin di-C-glycosides
(ACG1 and ACG2) based on reports by Kerscher & Franz (1987), Brazier-
Hicks et al. (2009) and Hamilton et al. (2009). 19
Figure 2.6 Location of DNA markers on chromosome 7B of Sunco x Tasman
(GrainGenes, accessed 22 September 2008). 23
Figure 2.7 Activation of structural genes of flavonoid biosynthesis by transcription
factors (Quattrocchio et al. 2006). A) The activity of R2R3-myb alone leads
to the induction of flavonol and phlobaphene biosynthesis genes. B)
Interaction between R2R3-myb, bHLH, and WD40 repeats (WDR) leads to
anthocyanin and proanthocyanin biosynthesis. 26
Figure 4.1. Frequency distribution for total apigenin di-C-glycoside (ACG) content and
composition in grain of 70 bread wheat, T. aestivum L, cultivars grown at
Turretfield, South Australia in 2005: A. Total ACG content in grain
(g/grain), B. Total ACG concentration (g/g), and C. Ratio ACG1/ACG2.
61
Figure 4.3 Content and composition of the 2 types of apigenin di-C-glycosides (ACG1
and ACG2) in the grain of the group 7 chromosome nullisomic-tetrasomic
lines of Chinese Spring compared with Cook, Ciano, Tasman, and Sunco.
The comparisons of the ACG1 and ACG2 content describe the differences in
ACG1 to ACG2 composition in the grain. White bars represent ACG1, red
bars represent ACG2. Bars represent SE of means. 71
Figure 5.1 Noodles and noodle sheets for measurements of b* andb*. A. YAN B.
WSN C. YAN sheet. B. WSN sheet. 82
xv
Figure 5.2 ACG concentration (g/g) in Buhler mill (white bar) and Quadrumat junior
mill (red bar) flour of 9 cultivars of bread wheat. The error bars represent the
standard errors. 94
Figure 5.3 Recovery (%) of grain ACG in Buhler mill (white bars) and Quadrumat
junior mill (red bars) flours for 9 cultivars of bread wheat. The error bars
represent the standard errors. 100
Figure 5.4 The trends of b* values between 0 to 24 hours measurements for varieties
that showed significant differences (p<0.001). 104
Figure 5.5 Standard curve relating change in YAN b* (b* = b*YAN with rutin –
b*YAN control) to the amount of added rutin (a flavone glycoside) at 0, 2, 4,
and 24. Green: b* at 0 hours, black: 2 hours, red: 4 hours, and blue: 24
hours. 100
Figure 6.1 The ACG traits in the parents of the Sunco/Tasman doubled haploid
population used for fine mapping. 126
Figure 6.2 Frequency distributions for ACG traits in the Sunco/Tasman doubled haploid
population used for fine mapping. The blue arrows indicated the means of the
trait for the parents (T: Tasman, S: Sunco). 127
Figure 6.3 Positions of the ASP and GSP primers for the SNP marker derived from the
BE352570 EST contig, I. The design of specific primer (LSP) (genome
specific primers that were re-used to amplify the specific EST locus), and
allele specific primer (ALS). B. The polymorphisms of the SNP marker
within BE352570 EST (573bp); II. typical banding patterns obtained with
some of the doubled haploid lines (#DH80 to #DH92). Bands scored as: A for
Sunco alleles and B for Tasman alleles. 133
xvi
Figure 6.4 SNP markers designed from BE445287 EST contig. I. The design of specific
primer (LSP) (genome specific primers were re-used), and 2 allele specific
primers (ALS). II. The polymorphisms of the first BE445287 SNP markers in
some of the doubled haploid lines (#DH54 to 68), III. The polymorphisms of
the second BE445287 SNP markers in some of the doubled haploid lines
(#DH31 to 43). Both markers were scored as A and B alleles: A for Sunco
alleles and B for Tasman alleles. 134
Figure 6.5 Order of markers on 7BS of Sunco/Tasman doubled haploid population
before and after fine mapping compared with the order in other genetic maps
(Synthetic/Opata (BARC), Chinese Spring/SQ1 and a Consensus map
(Somers et al. 2004) sourced from Graingenes databases (access 10 October
2011). Markers and arrows in red are the order of the markers before the fine
mapping, while those in blue are the ordered for the additional markers added
in this study. Markers in black are other markers in each chromosome that are
not in 7BS fine map. Numbering to the left of the chromosomes represents
genetic distance (cM). 137
Figure 6.6 QTL on 7BS for ACG1/ACG2 ratio analysed as a binary trait A/B (A: high
ratio, B: low ratio). Red line = LOD threshold at Fpr<0.001. 140
Figure 6.7 Comparative map of 7BS Sunco/Tasman, rice physical map 6S and rice
RI64/Azucena 6S. The markers and loci in red are markers that link 7BS and
rice 6S of physical map and markers that flank the QTL region in rice. Locus
in grey box: F2H, loci in red boxes: glycosyltransferases. Blue bar QACG-
7B: QTL for ACG trait at 7B, red bar Bph: QTL for brown plant hopper
resistance. Numbers on the left of Sunco/Tasman 7BS and rice IR64/Azucena
maps show the genetic distance between markers (cM), while those on the
xvii
left of rice physical map 6S show the distancein kilo base pairs (kb). On the
Sunco/Tasman map, 3.1cM is the distance between SNP marker BE352570
and wmc76, nearest marker to ratio QTL, while 5.5 cM is the size of the
chromosome interval between wmc426 and sun16. Information on the rice
physical map 6S and rice RI64/Azucena 6S genetic map was obtained from
the Gramene database. 145
Figure 6.8 Comparison of Sunco/Tasman 7BS with the physical map of rice 8L
(Gramene database). The 7BS marker in red is the wheat EST SNP marker
used to link the two maps. The blue bar marked QACG-7B is the QTL region
on 7BS for ACG traits (Table 6.3). 146
Figure 6.9 Comparison of the Sunco/Tasman 7BS genetic map, with the Brachypodium
distachyon physical map of chromosome 1 and the rice physical map of 6S
(Gramene database). Loci in red indicate the linkage between maps. The
arrows show the order of the loci. The physical maps are based on
information from Gramene database. Blue bar QACG-7B: QTL for ACG
traits at 7BS. Numbers on the left of Sunco/Tasman 7BS show the genetic
distance between markers (cM), while those on the right of Brachypodium
distcahyon and rice physical maps show distance in kilo base pairs (kb). 149
Figure 6.10 Comparison of the maps for Sunco/Tasman genetic map 7BS, Aegilops
tauschii 7D (Reference map of Dvorak (2009), Brachypodium distachyon
chromosome 3 (Comparative map 0.1, and physical map (Gramene Release
31) were obtained from Gramene database). Blue bar QACG-7B: QTL for
ACG trait at 7BS. Marker in red (BE445287) at 7BS Sunco/Tasman link this
population map to A. tauschii reference map, which structural relationship
with the Brachypodium distachyon comparative map has been established.
xviii
Red lines showed the links, while markers in yellow boxes are the markers
that link the A. tauchii reference map and the Brachypodium distachyon map.
The purple lines show the relationship between the wheat EST in the wheat
map and annotated EST cluster in the Brachypodium map. 150
Figure 6.11 Phylogenetic tree of the putative UDP-glycosyltransferases in the region of
rice chromosome 6 that is syntenic with the ratio QTL on Sunco/Tasman
compared with other UDP-glycosyltransferases: Bz1-W22 (Maize UDPG-
flavonoid 3-O-glucosyltransferase), BRADI1G43410.1 and Sb10g010640.1
(Brachypodium distacyon and Sorghum bicolour glycosyltransferases that
were the orthologs of rice C-glycosyltransferase (OSCGT,
LOC_Os06g18010.1), UGT71G1(Medicago truncatula flavonoid/triterpene
O-glucosyltransferase, VvGT5 (Vitis vitifera UDP-glucuronic acid:flavonol-
3-O-glucuronyltransferase), VvGT6 (Vitis vitifera bifunctional UDP-
glucose/UDP-galactose: flavonol-3-O-glucosyl/galactosyltransferase) and
VvGT1 (Vitis vitifera UDP-glucose:flavonoid 3-O-glycosyltransferase). The
cereal protein sequences were obtained from Gramene website, while the
other protein sequences were obtained from NCBI databases. Blue box: first
clade, red box: second clade.
153
Figure 6.12 Conserved region of the Plant Secondary Product Glycosyltransferase
(PSPG) motif of the putative UDP-glycosyltransferases from the region of
rice chromosome 6 that is syntenic with the ratio QTL on 7BS of
Sunco/Tasman. N and C at the x axis of the weblogo showed the direction
from N-terminal to C-terminal of the protein sequence; the height of the letter
stacks showed the conservation of the amino acid, and the height of the letters
xix
within the stack indicates the relative frequency of each amino acid at that
position. The arrow shows the amino acid polymorphism for UDP-glucose
recognition and UDP-galactose recognition (D). The D463H mutation
converted the bifunctional UDP-glycosyltransferase to a monofunctional
galactosyltransferase (Kubo et al. 2004, Offen et al. 2006, Ono et al. 2010,
Osmani et al. 2009). 154
Figure 6.13 Model of VvGT1 and position of the amino acid highlighted in
supplemental material 6.12. The red-maroon ribbons show the -helix
structure position, while the white ribbon shows the -helix and loop
structure position. The dark blue ribbon shows the position of the PSPG
motif. Small segments of the ribbon in red, purple and gold colour show the
positions of the amino acid polymorphism, while those in light blue, green
and yellow show the position of the conserved amino acids. The ball and
stick structure in the middle of the stereo molecule are the flavonoid and
UDP-glucose substrate molecules. The VvGT1 backbone was re-drawn from
the PDB file for the UDP-glucose: flavonoid 3-O-glycosyltransferase of
VvGT1 (2CIX) (Offen et.al. 2001) and this file was obtained from RSCB
Protein Data Bank (http://www.rcsb.org/pdb/home/home.do). The 3D
secondary structure was re-drawn from Osmani et al. (2009), while the
conservation and polymorphism of amino acids were drawn from Shao et al.
(2005). Information for the protein domain, family and functional sites of the
plant O-glycosyltransferases were downloaded from Prosite database of
ExPASy Swiss Institute of Bioinformatics (SIB) Bioinformatics Resource
Portal (http://prosite.expasy.org/), while the correlation between the multiple
alignments and the structural information of the PDB file were obtained from
xx
the S2C facility (http://www.fccc.edu/research/labs/dunbrack/s2c). Further
details are explained in the text. 155
Figure 7.1 Multiple alignments of translated protein of putative CGT:
LOC_Os06g18010 (Japonica rice OSCGT, Brazier Hicks et al. 2010),
Os06g0288300 (Indica rice glycosyltransferase), BRADI1G43410
(Brachypodium distachyon glycosyltransferase), Sb10g010640 (Sorghum
bicolor glycosyltransferase), GRMZM2G162783 (Zea mays
glycosyltransferase) and BJ215997 (wheat EST homologous to rice C-
glycosyltransferase). Blue arrows showed the position of the degenerated
primers: F1, F2, and F3 are forward primers, while R1, R2 and R3 are reverse
primers. The red lines in dash are the start and end of the primer sequences.
The grey and black shades showed the sequence conservation. 166
Figure 7.2 Multiple alignments of translated protein of putative F2H, FS2 and IFS:
LOC_Os06g01250 (Japonica rice F2H, Du et al. 2010), FS2Mt (Medicago
truncatula F2H, Zhang et al. 2007), F2HGe (Glycyrrhiza echinata F2H,
Akashi et al. 1998), F2HCs (Camellia sinensis FS2 (O. Kuntze, unpublished-
NCBI database)), IFSPs (Pisum sativum IFS, Cooper 2005), IFSTp (Trifolium
pratense IFS (Kim et al. 2005, unpublished-NCBI database)), IFS2Vu (Vigna
unguilata IFS2, Kaur & Murphy 2010), IFSPm (Pueraria montana var.
lobata IFS, Jeon and Kim (unpublished-NCBI database)). The F2H and IFS
sequences are sorted into 2 different groups: the conserved sequences of IFS
are highlighted in green, while while the contrasts between F2H/FS2 against
IFS sequences groups are shaded in purple. The conserved regions of both
groups are in black. Blue arrows show the position of the degenerate primers:
F1, F2, and F3 are forward primers, while R1, R2 and R3 are reverse primers.
xxi
The red boxes are the position of the primers: F1-F3 are forward primers,
while R1-R3 are reverse primers. The blue arrow and red lines in dash
between 471-481kb are the start and end of the cystein heme-iron ligand
signature of the cytochrome P450 protein motif. 167
Figure 7.3 A. Results of PCR amplification with primer F3 and R2, DNA of wheat
(Chinese Spring) was used as the template. Lane M: 1 kb plus DNA ladder as
marker (100-5000 numbers in white are their size); Lane 1-6: bands obtained
from 35 extension cycles of PCR with gradient temperature (15oC, every 30
second between 36oC-44oC). B. The results of EcoRI restriction, when the
band resulted from amplification with similar primer pairs with different
wheat DNA samples of nullisomic-tertrasomic lines of Chinese Spring were
cloned in p-Drive cloning vector. The bands at 480bp were the inserts, while
the bands at 3.85kb were the p-Drive vectors. Lane M: 1 kb plus DNA ladder
as marker. Lane 1: nullisomic 7B tertrasomic 7D lines, lane 2, 4 and 5: 7D7B,
3: 7A7B, 6: 7B7A. 174
Figure 7.4 Results of Nested PCR amplification: A. First stage of PCR amplification by
CGTF1R1 primer pair with Chinese Spring gDNA as template, lane M: 1 kb
plus DNA ladder as marker (numbers in white are in kb size), lanes 1, 3, 4
and 6: amplification products, with red rectangles showed the position of the
expected amplified bands (1050kb), that were excised prior to purification. B.
Second stage of PCR amplification by CGTF3R2 primer pairs with gDNA of
Chinese Spring and rice as template, lane M: 1 kb plus DNA ladder as marker
(numbers in white are in kb size), lane 1: positive control, the band obtained
from amplification of gDNA with CGTF3R2 primer pair without the first
stage nested PCR amplification, lane 2 and 3: bands obtained after 2 stages of
xxii
nested PCR amplification of Chinese Spring gDNA template with
CGTF1R1and CGTF3R2 primer pairs, lane 4 and 5: bands obtained after 2
stages of nested PCR amplification of rice gDNA template with
CGTF1R1and CGTF3R2 primer pairs. 175
Figure 7.5 Results of PCR optimisation for CGTF3R2, CGTF2R2 and CGTF1R2
primer pairs with cDNA as template. The cDNA were constructed from
mRNA isolated from embryo and seed coat of Sunco and Tasman parents. A.
PCR optimized for CGTF3R2 primer pair. cDNA templates: 1,2: Sunco
embryo; 3-4: Tasman embryo; 5-6: Sunco seed coat; 7 and 8 were rice and
Chinese Spring wheat as positive controls respectively; 9: water as negative
control B. PCR optimized for CGTF2R2 (2-6, 11, 12) and CGTF1R2 (7-10,
13, 14) primer pairs. cDNA templates: 2, 7: embryo of Sunco; 3, 8: embryo
of Tasman; 4, 9: seed coat of Sunco. Rice (5 and 10) and Chinese Spring
DNA (6) were used as positive controls. M: DNA ladder marked with kb in
white. 177
Figure 7.6 Results of re-amplification of PCR products of F3R2 primer pairs with
cDNA template of mRNA from embryo of Sunco (1, 2) and Tasman (3, 4).
M: DNA ladder marked with kb in white). 178
Figure 7.7 Multiple alignments of DNA sequences, obtained from PCR amplification
with genomic DNA template (sequences coded wheat1) and cDNA template
(sequences coded wheat2 and rice2). Sequence codes: sequence1, sequence2,
sequence3, sequence4, sequence5 and sequence6 indicated the identification
of the E.coli clones. The sequences in the blue rectangle show the position of
the F3 and R2 primer in each sequence. The grey and black shades show the
xxiii
sequence conservation. Alignment was performed by MAFFT online
alignment tools in http://www.ebi.ac.uk. 180
Figure 7.8 Multiple alignment of translated protein sequences, which nucleotides
obtained from PCR amplification with gDNA template (sequences coded
wheat1) and cDNA template (sequences coded wheat2 and rice2). Sequence
codes: sequence1, sequence2, sequence3, sequence4, sequence5 and
sequence6 indicated the identification of the E.coli clones. The amino acid
sequences in the blue rectangle show the position of the F3 primer in each
sequence. The grey and black shades show the sequence conservation.
Alignment was performed by MAFFT online alignment tools in
http://www.ebi.ac.uk. 181
Figure 7.9 Multiple alignment of translated protein sequences, which nucleotides
obtained from PCR amplification with gDNA template (sequences coded
wheat1) and cDNA template (sequences coded wheat2 and rice2). Sequence
codes: sequence1, sequence2, sequence3, sequence4, sequence5 and
sequence6 indicated the identification of the E.coli clones. The amino acid
sequences in the blue rectangle show the position of the R2 primer in each
sequence. The grey and black shades show the sequence conservation.
Alignment was performed by MAFFT online alignment tools in
http://www.ebi.ac.uk. 182
Figure 7.10 Alignment of protein sequences of wheat ESTs CA699411and CV773251
that have similarity to the N-terminal domain of rice CGT. 183
Figure 7.11 Alignment of protein sequences of wheat ESTs BJ215997, CJ606358, and
CJ711440 that have similarity to the C-terminal domain of rice CGT. 187
xxiv
Figure 8.1 Proposed model for ACG biosynthesis in bread wheat grain. The rice genes
are shown in red. 193
xxv
List of Supplemental Materials
Supplemental material 3.1 ACG concentration (g/g) for parents of existing doubled
haploid populations. Bars represent SE of means. From the top to the bottom:
ACG1 concentration, ACG2 concentration and Total ACG concentration
197
Supplemental material 3.2 ACG content in the grain (g/grain) of parents of existing
doubled haploid populations. Bars represent SE of means. From the top to the
bottom: ACG1 content, ACG2 content and total ACG content. 198
Supplemental material 3.3 ACG composition (ACG1/ACG2 ratio) in grain of parents of
existing doubled haploid populations. Bars represent SE of means. 199
Supplemental material 3.4 Layout of Sunco/Tasman doubled haploid population trial at
Narrabri, New South Wales, Australia. The Sunco and Tasman parent lines
were planted alternately, as one plot for every 20 plots of doubled haploid
lines. Information on this layout was provided by Assoc. Prof. Daryl Mares.
200
Supplemental material 3.5 The frequency distribution of ACG1/ACG2 ratio in 2 sets of
Sunco/Tasman doubled haploids. The black lines represent the old
population, the red lines represent additional lines, and the dashed grey lines
represent the distribution of the whole data set. The blue arrows indicate the
means of the ratio trait in the parents (T: Tasman, S: Sunco). 201
Supplemental material 4.1 List of germplasm and its origin used in this study together
with data for ACG1, ACG2 and Total ACG content (mg/g and mg/grain); and
ACG1/ACG2 ratio. 202
xxvi
Supplementary material 4.2 Chromatogram obtained for neutral hydroxylamine extract
of T. aestivum cv Sunco. The peaks corresponding to the two types of the
apigenin C-di-glycosides (ACG1 and ACG2) are indicated by arrows. 206
Supplemental material 4.3 100 grain weight, ACG consentration, ACG content and
ratio ofsome variaties that were grown both in the field and in the glass
house. Blue box: in the field; red box: inthe glass house, bars represnt SE of
means. 207
Supplemental material 4.4 Means (+ SE) of total ACG content (g/grain) of nullisomic
(N)-tetrasomic (T) lines Chinese Spring (A) and Chinese Spring/Triticum
spelta substitution lines (B). a-n: a-i: indicate significant differences (p<0.01)
in total ACG content based on Tukey test of multiple comparison at 5% level.
209
Supplemental material 4.5 Pedigree of Sunco and its relatives as drawn from (Martynov
& Dobrotvorskaya 2006). 210
Supplemental material 4.6 Pedigree of Tasman and its relatives as drawn from
(Martynov & Dobrotvorskaya 2006). 211
Supplemental material 5.1 Proportion and ratio of ACG1 and ACG2 in grain and
Quadrumat Junior mill flour. 212
Supplemental material 5.2 Proportion (%) of Lutein in grain and Quadrumat Junior mill
flour. 213
Supplemental material 5.3 ACG content and recovery in Buhler Mill flour fractions.
214
Supplemental material 5.4 Comparison of changes in theL* (YAN-WSN, red lines
and markers) and b* (YAN-WSN, black lines and markers) at 0, 2, 4 and 24
xxvii
hours. A: Sunvale, B:Sunco, C: Krichauff, D: GBA Ruby, E: Carnamah,
F:Reeves. 215
Supplemental material 6.1 Genetic map of Sunco/Tasman doubled haploid population
re-constructed with 361 markers and 153 lines of the population. The bars
next to the 2B, 4A, 4B, 4D and 7B maps show the QTL location: ACG1
concentration (g/g) (dark blue), ACG2 contentration (g/g) (black), ACG1
content (g/grain) (green), ACG2 content (g/grain) (pink), ACG1/ACG2
ratio (brown), 100 grain weight (red), total concentration (g/g) (gold) and
total content (g/grain): bright blue. 216
Supplemental material 6.2 QTL for ACG traits and 100 grain weight in Sunco/Tasman
doubled haploid population. QTL Test Profiles of the whole genome scan
with cofactors (CIM) function in GENSTAT 14. A. QTL for ACG1
concentration (μg/g), B. QTL for ACG2 concentration (μg/g), C. Total QTL
concentration (μg/g), D. QTL for ACG1/ACG2 ratio, E. QTL for ACG1
content (μg/grain), F. QTL for ACG2 content (μg/grain) G. QTL for Total
ACG content (μg/grain), H. QTL for 100 grain weight (g). For the QTL
effect, blue: Sunco effect, red: Tasman effect. 221
Supplemental material 6.3 Analysis of polymorphic markers located on 7BS of
Sunco/Tasman doubled haploid population; ns = not significant; *: significant
(p<0.001, Fpr = 3.841). 223
Supplemental material 6.4 QTL for ACG content and composition detected on 7BS of
the Sunco/Tasman doubled haploid population by Composite Interval
Mapping (CIM) after the original map was saturated with more SSR markers.
A. ACG1 concentration (μg/g), B. ACG1 content (μg/grain), C. ACG2
xxviii
concentration (μg/g), D. ACG2 content (μg/grain) and E. Ratio of
ACG1/ACG2. Red line = LOD threshold at Fpr<0.001. 224
Supplemental material 6.5 Protein sequences coded by genes located in the region of
rice chromosome 6 that is syntenic to the 7BS QTL for ACG traits in
Sunco/Tasman (Gramene databases accessed 19 January 2010). 225
Supplemental material 6.6 Protein sequences coded by genes located in the region of
rice chromosome 8 that is syntenic to the 7BS QTL for ACG traits in
Sunco/Tasman (Gramene databases accessed 19 January 2010). 228
Supplemental material 6.7 Synteny of Sunco/Tasman doubled haploid chromosome 4B
region harbouring minor QTL for total ACG1 and ACG2 content with the
physical maps of Chinese Spring wheat and rice chromosome 3. 231
Supplemental material 6.8 Wheat 3B sequences that show interrupted synteny of wheat
7BS and rice 6 (Gramene, access 27 April 2012). 232
Supplemental material 6.9 Synteny between 7BS of wheat and Brachypodium
distachyon at BRADIG43410 locus (115bp) (red box). Genome Browser for
7BS_Syn_Build_0.1:577734..597734 was taken from
www.wheatgenome.info/. 234
Supplemental material 6.10 Synteny block between Brachypodium distachyon
chromosome 1 and rice chromosomes 6 and 10. Illustration was taken from
Gramene database (accessed 11 March 2012). Blocks in blue colour are
synteny block between rice chromosme 6 and the Brachypodium chromsome
1, while the large white chromosome is the Brachypodium distachyon
chromosome 1. Small red rectangle in the Brachypodium distachyon
chromosome shows the location of syntenic SNP marker BE352570. 235
xxix
Supplemental material 6.11 Synteny block between Brachypodium distachyon
chromosome 3 and rice chromosomes 8 and 10. Illustration was taken from
Gramene database (accessed 11 March 2012). Blocks in blue colour are
synteny block between rice chromosme 8 and Brachpodium chromosome 3,
while the large white chromosome is the Brachypodium distachyon
chromosome 3. Small red rectangle in the Brachypodium distachyon
chromosome shows the location of sythenic SNP marker BE445287. 236
Supplemental material 6.12 Multiple alignments of the UDP-glycosyltransferases from
the region of rice chromosome 6 than is syntenic with the Ratio QTL on 7BS
of Sunco/Tasman with other UDP-glycosyltransferases. The sequences are
similar to that shown in Figure 14. Secondary structure conservation shown
by pink (-helix) and yellow (-helix) shades. The red arrows shows His-33
and Asp-163 residues that are catalytically important for interaction with
UDP-sugar, while the blue arrow shows the single amino acid polymorphism
between the putative O-glycosyltransferases and C-glycosyltransferases. The
alignment is available on the next page. 237
xxx
Summary
Colour is an important determinant of quality and customer appeal for Asian noodles
that are made from bread wheat (Triticum aestivum L.). The Asian noodle market
represents approximately one third of wheat exports from Australia and as a
consequence maintaining and improving colour for noodles is an important research and
breeding objective. The focus of this project is yellow alkaline noodles (YAN) prepared
using wheat flour and alkaline salts, sodium and potassium carbonate, and for which a
bright yellow colour is desired. Xanthophylls, primarily lutein, and apigenin di-C-
glycosides (ACGs) have been shown to be important components of this yellow colour.
ACGs were of particular interest since, in contrast to lutein, the content in flour could
be increased without adverse effects on colour of other end-products. There was little
information either on the genetic variation for ACG content or the mechanism and
genetic control of biosynthesis which was surprising in view of their putative role in a
wide range of plant processes, food colour and flavour, and possibly human health.
The aims of this project were to provide new information on the role of ACGs in YAN
colour and genetic regulation of their biosynthesis. To achieve this aims: genetic
variation in grain ACG traits in bread wheat and related species was surveyed, the
quantitative contribution of ACG to the yellow colour of YAN was determined and
compared to lutein, QTL for ACG content and composition were located, and
candidate genes associated with variation in ACG composition identified.
Substantial variation in both grain ACG content and the ratio, ACG1/ACG2, were
identified within bread wheat cultivars and related species. Genotype controlled the
xxxi
major portion of the variation. ACG content appeared to be a multigenic trait whereas
variation in ACG1/ACG2 was associated with a limited number of chromosomes, in
particular chromosomes 1B, 7B and 7D. In the absence of chromosome 7B (Chinese
Spring 7B nullisomics) there was a substantial increase in ACG1/ACG2, i.e. a relative
increase in the glucose-containing isomer, possibly indicating the presence of a C-
glycosyltransferase on 7B with specificity for UDP-galactose. A similar phenotype
observed in some wheat cultivars could be explained by a deletion or mutation of a gene
controlling this enzyme. The results suggest that it should be possible to manipulate
both ACG content and composition through breeding.
Only 30% of ACG (means 19.3g/g) is recovered in flour, which contributed to 1 to 3
CIE b* units to the part of the yellow colour of yellow alkaline noodles (YAN) that
develops specifically in the presence of alkali. The relatively low recovery of ACG in
flour contrasts with the high recovery of lutein (90%, with means 1.011g/g). Since the
difference between white salted noodles (WSN) and YAN is approximately 6 b* units,
this would indicate that another unidentified compound(s) is responsible for the
difference. Potential for ACG0-based improvement of bread wheat cultivars for YAN
yellowness is likely to be limited by the range of genetic variation, the location of ACG
in grain tissues that are largely discarded during milling and the lack of correlation
between grain and flour ACG content. Moreover, the observed variation in ACG
recovery in small scale milling was not reflected in larger scale milling anticipated to
better represent commercial practice. The improvement in flour recovery and the
amount of ACG recovered in the flour were not significant and not enough to achieve
the yellowness of commercial noodles. Selection that requires larger scale milling is
costly, time consuming and not applicable to early generation screening. In this context,
xxxii
further work on QTL associated with variation in ACG content and development of
marker-assisted-selection would be very useful.
Addition of thirteen new markers to the QTL region for ACG trait on chromosome 7BS
in a Sunco/Tasman doubled haploid population reduced the size of the QTL interval
from 28.8cM to approximately 5.5cM. In this revised 7BS map, the major QTL for
ACG1 and ACG2 content as well as ACG1/ACG2 ratio were detected within 4.7cM of
SSR marker Xwmc76. The QTL region linked to Xwmc76 was shown to be syntenic
with a region in rice chromosome 6S between AP005387 and AP005761 and a region
on Brachypodium chromosome 1. Based on these comparisons, the most likely
candidate gene associated with variation in ACG composition appeared to be a
glycosyltransferase. Alternate alleles at the 7BS QTL may be associated with amino
acid changes within the C-glycosyltransferase that shift the substrate specificity from
galactose (ACG2, Tasman) to glucose (ACG1, Sunco). Alternatively, based on a
comparison of Chinese Spring nullisomic-tetrasomic lines where nullisomic 7B was
associated with a phenotype similar to Sunco, it is possible that Sunco contains a null
allele. Other candidate genes located on the same chromosome that could potentially be
involved in ACG biosynthesis were identified and included a sugar transporter, which
could determine the relative sizes of the available pools of UDP-glucose and UDP-
galactose, an epimerase required for inter-conversion of these sugars, other
glycosyltransferases and a flavone-2-hydroxylase (F2H) involved in the first committed
step in the pathway to ACG.
Research approaches that could be used to validate the role of the candidate gene are
discussed along with other options for improving the colour of wheat cultivars for the
xxxiii
YAN market. Options for utilizing ACG as yellow pigment of noodles might include
incorporating the embryo or seed coat materials (pollard and bran) into the flour after
milling and genetic modification of bread wheat to achieve ACG expression in the
starchy endosperm.
xxxiv
Statement of Authorship
This work contains no material which has been accepted for the award of any other
degree or diploma in any university or other tertiary institution and, to the best of my
knowledge and belief, contains no material previously published or written by another
person, except where due reference has been made in the text.
I give consent to this copy of my thesis, when deposited in the University Library, being
made available for loan and photocopying, subject to the provisions of the Copyright
Act 1968.
The author acknowledges that copyright of published works contained within this thesis
(as listed below) resides with the copyright holder(s) of those works.
I also give permission for the digital version of my thesis to be made available on the
web, via the University’s digital research repository, the Library catalogue, the
Australasian Digital Theses Program (ADTP) and also through web search engines,
unless permission has been granted by the University to restrict access for a period of
time.
Grace Yasmein Wijaya
November 2012
xxxv
List of Publications
Wijaya GY, Asenstorfer R & Mares D 2010, 'Flavone-C-diglycosides and lutein in
wheat grain: their contribution to the yellow colour of alkaline noodles', in: C
Blanchard, D Pleming & H Taylor (eds), Cereal 2009: Proceedings of the 59th
Australian Cereals Chemistry Conference, Wagga Wagga, New South Wales, Australia,
27-30 September 2009, Royal Australian Chemistry Institute, pp. 162-164.
Wijaya GY, Asenstorfer RA & Mares DJ (2010), ‘Genetic control of C-glycosylation in
the biosynthesis pathway of flavone-C-diglycosides, yellow colour substance of alkaline
noodles, in bread wheat’. Molecular Life- from discovery to Biotechnology, Ozbio 2010
(ASBMB conference in conjuction with the 12th IUBMB conference and FAOMB),
Melbourne, 26 September-1 October 2010.
Wijaya GY, Mather DE, Brave M, Wu H, Walker AR, Chalmers KJ & Mares DJ 2012,
‘QTL associated with variation in apigenin-C-diglycoside content and composition of
bread wheat (Triticum aestivum L.) grain and the identification of candidate genes’,
Molecular Mapping and Marker assisted Selection International Conference, Vienna,
8-11 February 2012.
Wijaya GY & Mares DJ 2012, ‘Apigenin di-C-glycosides (ACG) content and
composition in grains of bread wheat (Triticum aestivum) and related species’, Journal
of Cereal Science 56 (2): 260-267.
xxxvi
Acknowledgement
I would like to acknowledge and sincerely thank my principal supervisor Associate
Professor Daryl Mares and my external supervisor Dr Mandy Walker (CSIRO Plant
Industry) for support, supervision and learning experiences during my candidature.
Their expertise, dedication, insight, and critical comments are highly valuable and
inspiring for the completion of this research project and PhD candidature. I am indebted
to them for the opportunities they have provided for me to develop research skills.
I would like to express my sincere gratitude to Professor David Coventry as my mentor,
Professor Richard Russel as Dean of Graduate Study, Professor Gurjeet Gill as
Postgraduate Coordinator, Niranjala Seimon as Australian Development Scholarship
liaison officer and Jane Copeland (International Student Advisor at the Waite) for their
supports during my candidature. This thesis will not be finished without their advice
and guidance during the difficult and challenging times.
I would like to thank Professor Diane Mather for her valuable advice, critical comments
and technical support during the molecular marker experiments and chapter writing and
Dr. Robert Asenstorfer for his advice and assistance during the biochemistry
experiments and for setting up the HPLC machine.
I gratefully acknowledge the receipt of an Australian Development Scholarship (ADS)
from Australian Government for funding and Atma Jaya Catholic University of
Indonesia for study leave permission. I thank Professor Antonius Suwanto (Dean of
Biotechnology Faculty 2002-2009) for advice and support during preparation of this
xxxvii
study leave and Professor Maggy T. Suhartono (PhD mentor) for advice, support and
guidance from the preparation until completion of this degree.
Acknowledgement also goes to Associate Professor Ken Chalmers and Dr. Paul
Eckermann for consultation on the mapping data and their statistical analyses.
In addition, I would like to thank also:
Kerrie Willsmore, Anke Lehmensiek and Greg Lott for the initial Sunco/Tasman
mapping data.
Kerrie Willsmore and Judy Cheong for preliminary map and QTL analyses on
7BS in 2005.
Mrinal Bhave and Humei Wu (Faculty of Life Sciences, Swinburne University
of Technology) for additional markers information to the initial Sunco/Tasman
mapping data.
Klaus Oldach (SARDI) and Bao Lam Hyunh for information on the wheat
sequence and genome database and technical aspect in utilizing them.
Matthew Hayden (Victoria DPI) for information on SNPs in Sunco x Tasman
7B chromosome and Julien Bonneau for information on SSR markers databases
and their access.
Dr. Nilangani Pathirana: for information on Wheat EST Databases.
Judy Rathjen, Christine Kuznir and Hyunn Law for technical assistance and
friendship during my work with cereal biochemistry laboratory.
Elise Tucker and Elyssia Vassos for technical assistance during my time in the
molecular marker laboratory.
xxxviii
Karin Sefton and Erika Cavalini for technical assistance during my time with
flavonoid group of CSIRO Plant Industry.
I especially thank my mother for her continuous prayers, love, understanding,
encouragement and support throughout my absence for her, from the preparations to the
completion of this PhD candidature. I thank also my family, my friends, my friends’
family and friends of my family that would be too many to be mentioned one by one;
for their prayers, encouragement and love. I am indebted to them all for the strength and
courage to finish this PhD candidature and to survive my life journey.
xxxix
List of Abbreviations
2-ODDs 2-oxoglutarate-dependent dioxygenases
ACG apigenin di-C-glycosides
ACG1 apigenin-6C-arabinoside-8C-glucoside (isoschaftoside)
apigenin-6C-glucoside-8C-arabinoside (schaftoside)
ACG2 apigenin-6C-arabinoside-8C-galactoside
apigenin-6C-galactoside-8C-arabinoside
AFLP amplified fragment length polymorphism
AMD age-related macular degeneration
ANR anthocyanidin reductase
ANS anthocyanidin synthase
AS aureusidin synthase
BAC library bacterial artificial chromosome library
bHLH basic/helix-loop-helix
Bz-W22 O-glycosyltransferases: UDP-glucosyl and glucuronosyl transferase
of maize bronze alleles
cDNA complimentary DNA, synthesise from mRNA
CHI chalcone isomerase
CHS chalcone synthase
CIE Commission Internationale d'Eclairage
DArT diversity arrays technology
DFR dihydroflavonol-4-reductase
EBG early biosynthetic genes
EST expressed sequence tags
xl
F2H 2S-flavanone 2-hydroxylase
F3H flavanone-3β-hydroxylase
FCGT flavonoid C-glycosyltranferase
FLS flavonol synthase
FS1 flavone synthase 1
FS2 flavone synthase 2
GAT UDP-glucuronic acid:flavonol-3-O-glucuronosyltransferase
gDNA genomic DNA
GT glycosyltransferases
HPLC high performance liquid chromatography
IFS isoflavones synthase
LAR leucoanthocyanidin reductase
LBG late biosynthetic genes
LOX lipoxygenase
OMT O-methyltransferases
OsCGT C-glycosyltransferase of rice
PAC clone P1 artificial chromosome clone
PPO polyphenol oxidase
QTL quantitative trait loci
RFLP restriction fragment length polymorphism
RT rhamnosyl transferase
RT-PCR reverse transcription polymerase chain reactions
SDR short-chain dehydrogenase/reductases
SNP single nucleotide polymorphism
SSR simple sequence repeat
xli
UDP-galactose uridine 5′-diphosphogalactose
UDP-glucose uridine 5′-diphosphoglucose
UFGT UDP glycose:flavonoid-3-O-glycosyltransferase
UDPG flavonol 3-O-glucosyl transferase
VvGT1 UDP-glucose:flavonoid 3-O-glycosyltransferase with ability to
transfer UDP galactose in Vitis vitifera
VvGT5 UDP-glucuronic acid:flavonol-3-O-glucuronosyltransferase (GAT)
of Vitis Vitifera
VvGT6 UDP-glucose/UDP-galactose:flavonol-3-O-
glucosyltransferase/galactosyltransferase of Vitis Vitifera
WSN white salted noodles
YAN yellow alkaline noodles
Є-LCY Є-cyclase
1
Chapter I: General Introduction
1.1 Background
Australia exports up to 80% of its wheat production which can represent approximately
18% of world wheat trade (Mohanty et al. 1995). Asian countries located in the South
East Asia, East Asia, South Asia and Middle East are the biggest market for this wheat
(Ahmadi-Esfahani & Stanmore 1997). In Japan, Korea and South East Asian countries,
1/3 of this imported wheat is used in the manufacture of noodles (Miskelly 1993,
Wrigley 1994), with approximately 60% going into instant dried noodles, while the rest
is used for making wet and dried white salted noodles (WSN) or yellow alkaline
noodles (YAN).
There have been concerns with the wet noodle industry, especially with YAN, which is
popular as street food in Asia. It is produced on a small scale by home industries
scattered all over the country and widely distributed by traditional market food stalls,
night markets, street food sellers, vending machines and travelling food sellers. There
are no quality standards for the product, except the consumer preference for colour and
taste. Governments in the region have tried to make a national standard, but have
encountered difficulties because each noodle manufacturer has their own methods and
recipes that have been part of their family tradition and inheritance.
YAN yellowness and the stability of this yellow colour is critical to consumer and
market acceptance. To meet consumer preferences, noodle manufacturers may increase
the concentration of alkaline solution, which is detrimental to the elasticity and pasting
properties of the dough, or add colouring agents either natural or artificial which
2
influence the shelf-life of the noodles. To preserve the texture and lifetime of the
noodles, chemicals such as borax (sodium tetraborate decahydrate) and formaldehyde
have been known to be added to the dough (Khalik 2006) although these chemicals are
potentially harmful for human health. There is an increasing market demand in the
region for a reduction in the use of these additives and flour with inherent natural colour
suitable for noodle production would have significant marketing advantages.
1.2 Knowledge Gap
Previous studies of flour and noodles identified some of the substances that give natural
yellow colour to noodles such as the xanthophylls, primarily lutein, and apigenin di-C-
glycosides (ACGs). Xanthophylls and their role in bread and noodle colour have been
extensively studied. Increasing the xanthophyll content of wheat grain is one option for
improving YAN colour however this would be likely to compromise the use of wheat
flour in a wide range of other end-products, most of which are white to creamy in
colour (Moss 1967). There is also an opportunity to increase the level of ACGs in wheat
grain. However, in contrast with the numerous reports on xanthophyll content in grains,
flour and noodles from a wide range of wheat varieties, no quantitative results have
been reported for ACGs. Moreover, little is known regarding the genetic regulation of
ACG biosynthesis in wheat grain. This project aims to provide new information on the
role of ACGs in YAN colour and genetic regulation of their biosynthesis.
1.3 Structure of thesis
This thesis consists of 4 sections: the first section containing a general Introduction and
a review of literature, the second section containing the general methods that were used
throughout the study, the third section containing 4 experimental chapters and finally a
3
general discussion. The first experimental chapter discusses the genetic variation in
ACG content and composition in bread wheat cultivars and species, and the possible
chromosomal locations of the loci that control the trait genetically. A manuscript based
on this chapter has been accepted for publication by the Journal of Cereal Science. In
the second experimental chapter, the contribution of the ACGs to the yellow colour of
noodles is discussed, included its comparison to that of lutein and the effect of 2 milling
methods. The third chapter discusses the loci involved in the genetic control of ACG
content and composition, where a major highly significant QTL region for the ACG
traits at 7BS was fine mapped and the candidate genes were identified. Results from a
preliminary study to optimise the existing PCR based methods to isolate the candidate
genes are discussed in the fourth experimental chapter. Although the experiment has not
yet come up with satisfactory results, the future direction for further application and
optimisation of the methods are discussed.
4
Chapter II: Literature review
2.1 Asian noodles as one of the major end-products of Australian
bread wheat
There are 3 types of wheat-based Asian noodles that differ in the nature of raw material
used, the pH, processing methods and the organoleptic qualities. These are white salted
noodles (WSN), Yellow alkaline noodles (YAN) and instant noodles (Corke &
Bhattacharya 1999) (Table 2.1). In general, the basic ingredients for all of these noodles
are flour of bread wheat (Triticum aestivum), water, salt, and/or alkaline salt solution
(Miskelly 1996). These ingredients are mixed and then made into dough sheets by
passing through a series of smooth steel rolls prior to cutting into noodle strands (Nagao
1996).
Table 2.1 Types of noodles based on nature of raw materials used, pH and organoleptic
qualities (Corke & Bhattacharya 1999).
Types of Noodles Ingredients Noodle characteristics
White-salted noodles
(WSN)
flour of low to medium protein level
(8–10%), water (30–35%), sodium
chloride (2-3%). pH 6.5–7
soft elastic texture and a
smooth surface
Yellow-alkaline
noodles (YAN)
hard wheat flour of medium protein
content (10–12%), water (30–35%),
alkaline salts, e.g., sodium carbonate,
potassium carbonate; pH 9–11;
firm, chewy, springy
texture and bright yellow
appearance
Instant noodles wheat flour of medium protein
content (9–11%), water (30–35%),
common salt or alkaline salts (2–3%),
oil; pH 5.5–9
elastic, chewy texture
5
A flour characteristic that has an important influence on the choice by Asian countries
for Australian wheats for their noodles is colour (Miskelly 1993). Flour with clean
white colour is usually used for bakery products, while the bright white to creamy
yellow flour is used for noodle manufacture (Ryan 2005). In general prime hard and
Australian hard wheat grades, primarily from eastern Australia, are preferred for YAN
whilst Australian Standard Noodle wheat cultivars (ASN), primarily from Western
Australia, are used for WSN (Lush 2007, O'Brien et al. 2001).
Noodle consumers expect noodles to have a bright, clean appearance but there are
variations in the preference for levels of yellowness between regions (Miskelly 1993).
Differences in the yellow colour of flour between Australian wheat cultivars have been
reported (Mares 1991) and there is an opportunity to breed cultivars with higher natural
yellow flour colour especially for YAN.
2.2 Yellow colour of YAN
2.2.1 Natural Compounds that contribute to the yellow colour of YAN
2.2.1.1 Types of natural compounds that contributes to the yellow colour of
YAN and their roles in plants and human health
There are 2 groups of natural compounds that have been reported to contribute to the
yellow colour of YAN, xanthophylls and flavonoids (Mares & Mrva 2008). The
xanthophylls in YAN dough are mainly in the form of lutein. Strong positive
correlations have been reported between lutein content and the yellowness of noodles
(Humphries et al. 2004). The flavonoids that are found in wheat grain and flour are
mainly apigenin di-C-glycosides (ACGs) that are colourless at acid or neutral pH but
turn yellow at the higher pH used in the preparation of YAN (Asenstorfer et al. 2006).
6
The presence of ACGs in wheat grain and flour is related to yellow colour of noodles
but the correlation has not been quantified.
Xanthophylls (C40H54(OH)2) (Figure 2.1) are produced by the carotenoid biosynthetic
pathway with the immediate precursor being carotene (Howitt & Pogson 2006).
Besides their role as a plant pigment, these substances also benefit human health. In
flower petals, these substances provide a pale to deep yellow colour (Tanaka et al.
2008). In wheat endosperm, xanthophylls are present as lutein and give creamy colour
to the flour and end-products (Kaneko & Oyanagi 1995). The accumulation of lutein in
human retina is reported to contribute to a reduced incidence of retinal diseases,
particularly age-related macular degeneration (AMD) (Schalch et al. 2007).
Figure 2.1 Structure of lutein (all-trans Lutein) (Abdel-Aal et al. 2007).
Apigenin di-C-glycosides (ACGs) in plants along with anthocyanins, flavonols,
proanthocyanidins, aurones and phlobaphenes are flavonoids (Shirley 1998). Flavonoids
represent a large and diverse class of secondary metabolites present in plants. The
apigenin di-C-glycosides (ACGs) are a group of flavonoids that have been reported to
contribute to the yellow colour of Asian alkaline noodles made from bread wheat,
7
Triticum aestivum L., flour (Asenstorfer et al. 2006). As a consequence, they are a
potential target for wheat breeders attempting to develop new cultivars with improved
noodle colour. An increase in the levels of these endogenous compounds would enable
manufacturers to reduce the use of colour additives that are currently in common usage.
In addition, ACGs also have reputed roles as bioactive compounds in herbal tea
(McKay & Blumberg 2006) and curry powder (Satti et al. 2009), allelopathic
compounds against parasitism and microbial infections (Hooper et al. 2010, Omar et al.
2011), feeding inhibitors of insect pests (Stevenson et al. 1996), as UV-protectants (Les
& Sheridan 1990) and to have an-inflammatory and anticancer activity (Carvalho et al.
2010). However, despite their possible diverse and important roles for humans and
agriculture, little is known of their biological functions in plants and the biochemical
and genetic mechanisms that control their biosynthesis.
The ACGs are characterised by a common C6-C3-C6 flavone skeleton (Figure 2.2) with
3 carbons that are cyclized with an oxygen bridge between the 2 phenyl groups
(Cavaliere et al. 2005). There are 2 groups of ACGs differentiated by the hexose sugar
that is attached to the flavone A ring (Asenstorfer et al. 2006). The first group, ACG1,
consists of a pair of Wesseley-Moser regioisomers with glucose at either the 6th or 8th
carbon of the A ring of apigenin, while the second group, ACG2, consists of another
pair of Wesseley-Moser regioisomers that have galactose rather than glucose attached to
C6 or C8. In both ACGs, arabinose occupies the alternate carbon position not linked to
the hexose sugar. The ACG1 regioisomers are diasterioisomers of ACG2.
8
Figure 2.2 The general structure of flavones. ACGs are identified by sugar groups
attached to 8-C and 6-C (Asenstorfer et al. 2006).
2.2.1.2 Contribution of xanthophylls and ACGs to the yellow colour of
alkaline noodles
Xanthophylls and ACGs have different attributes in noodle dough. Xanthophylls are
present at relatively low concentration in bread wheat and give colour ranging from
white to pale yellow to noodle dough (Parker et al. 1998). On the other hand, the ACGs
remain colourless in water or acid solution and give the yellow colour only after the
alkaline solution is added during the making of YAN dough (Asenstorfer et al. 2006).
In wheat grain, these two compounds are located in different tissues which has a major
impact on their recovery in flour as the result of milling (Miskelly 1996). The
xanthophylls are located in embryo, grain coat and starchy endosperm; while the
flavones are located in embryo and seed coat (Asenstorfer et al. 2006, Fortmann &
Joyner 1978). The anatomy of wheat grain tissues are described in Figure 2.3.
9
Figure 2.3 Anatomy of wheat grain tissues (Anon 1960). Embryo, endosperm and grain
coat tissues comprise 2-3%, 81-84% and 14-16% of the grain respectively.
Epidermis
A NOTE:
This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.
10
2.2.2 Factors influencing the measurement of the yellowness of noodles
and the content of xanthophyll and ACG in wheat grain
Ideally, yellow alkaline noodles have a pale yellow colour (Kruger et al. 1994). High b*
(Miskelly 1984) when measured according to the three dimension colour (L*-a*-b*)
system proposed by the Commission Internationale d'Eclairage (CIE) (Wyszecki &
Stiles 1982). The value of b* shows the position of the sample on the yellow-blue axis
of the CIE 3-D colour space and a positive value indicates yellowness (Kruger et al.
1992). This yellowness is related to the sum of both carotenoid and flavonoid content
(Mares et al. 1977 in Mares & Mrva 2001). Humphries et al. (2004) reported a positive
correlation between b* value and carotenoid content in different groups of wheat grains
and noted the influence of non-carotenoid substances in decreasing the b* value when
grains from different wheat varieties are bulked.
Various methods have been published for the isolation, identification and quantification
of xanthophylls and ACGs. Routine analysis of these two compounds in wheat grain,
flour and noodle sheet can be performed by HPLC as described by Asenstorfer & Mares
(2006), Breithaupt & Bamedi (2001), Fortmann & Joyner (1978), Soriano et al. (2007).
However, in contrast with the availability of reports on xanthophyll content in wheat
grain, flour and noodles, no quantitative analysis has been reported for ACGs in similar
material.
Conditions of storage and timing are critical both for measurements of b* value and
quantification of xanthophylls and ACGs of noodles and wheat grain. With noodles, in
particular, the stability of the yellowness immediately after making the noodle sheet
depends on the wheat variety used (Asenstorfer et al. 2006). This is influenced by the
11
condition of the samples in relation to the activities of the oxidative enzyme polyphenol
oxidase (PPO), which result in darkening of noodles (Baik et al. 1995, Davies &
Berzonsky 2003, Fuerst et al. 2006a, Mares & Mrva 2001) and lipoxygenase (LOX) that
oxidises polyunsaturated fatty acids such as linoleic acid to hydroperoxides, which in
turn are responsible for the oxidative degradation of yellow pigments such as lutein and
carotene (Mares & Mrva 2008). The activities of PPO (darkening) masks the
brightness and yellowness and is reflected the measurement of b* and L* values of
noodles (Hessler et al. 2002, Mares & Mrva 2008, Pourcel et al. 2005). Similarly, LOX
results in bleaching of yellow colour due to lutein and a reduction in b*.
In developing wheat grains, ACG in the embryo increased whilst that in the seed coat
decreased with time after flowering (Ingram 2006, Rathjen 2006). The time of
harvesting in terms of days post anthesis is therefore critical for analysis of ACG in
grain and noodle sheets (Ingram 2006). In the case of xanthophyll measurement, the
content of free lutein in wheat grain decreased slowly with time after harvest depending
on the storage conditions, which determine the extent of esterification of lutein with free
fatty acids (Soriano et al. 2007).
2.2.3 The amount, tissue location and composition of xanthophylls and
apigenin di-C-glycosides in wheat grain and recovery in flour following
milling
Variations has been found in total ACG content in grain of a limited number of wheat
varieties (Asenstorfer et al. 2006). In addition, measurement of ACG content in
wholemeal flour of several Australian wheat varieties shows that Sunco and Sunvale
have significantly different proportions of the ACG1 and ACG2 when they are
12
compared with Angus, Avocet, and Canna (Asenstorfer et al. 2006). Amongst the
Australian wheat varieties used by Rathjen (2006), SUN325 has the highest content of
ACGs in the seed coat.
The yellow pigment content in the flour of different wheat varieties is influenced by
milling (Adom et al. 2005, Chakraborty et al. 2003, Kuchel et al. 2006, O'Brien et al.
1993, Parker et al. 1999). ACGs are located in germ (Asenstorfer et al. 2006, Hatcher et
al. 2008) and bran but are absent from the endosperm (Asenstorfer et al. 2006). Their
availability in the flour that is used in noodle making, is the result of contamination by
both germ and bran tissues during milling (Miskelly 1996). Milling can influence the b*
value of flour and noodles even though the concentration of ACGs in the grain is the
same. The amount of bran and germ and therefore ACGs in the flour depend on the
physical structure and the milling qualities of the grain (Marshall et al. 1984, Oliver et
al. 1993). Both are genetically controlled and influenced by environmental conditions
(Graybosch et al. 2004, Oliver et al. 1993). On the other hand, xanthophylls are found in
most parts of the wheat grain. The germ tissues contained the highest xanthophyll
concentrations (Soriano et al. 2007), however, most of xanthophylls in wheat flour
recovered from milling originates from the starchy endosperm that constitutes most of
the flour (Marshall et al. 1984, Zhang et al. 2005). Therefore, in contrast to ACG their
presence in flour is not dependent on contamination during milling.
2.3 Apigenin di-C-glycoside biosynthesis in plants
2.3.1 Flavonoid biosynthetic pathway
Apigenin di-C-glycosides (ACGs) in plants are produced by the flavonoid metabolic
pathway. This pathway consists of a number of branches that produce distinct groups of
13
compounds (Quattrocchio et al. 2006) (Figure 2.4). There are several families of
enzymes that function and interact with each other in the pathway, including the
cytochrome P450 hydroxylases, the 2-oxoglutarate-dependent dioxygenases (2-ODDs),
the short-chain dehydrogenase/reductases (SDR), the O-methyltransferases (OMT), and
the glycosyltransferases (GT) (Himi & Noda 2006). The enzymes that function in the
early part of the pathway such as chalcone synthase (CHS) and chalcone isomerase
(CHI) are known to interact with those that initiate the branches of the pathway such
as dihydroflavonol-4-reductase (DFR) and flavanone-3β-hydroxylase (F3H) (Hrazdina
& Wagner 1985). Structurally, these proteins form a globular complex that is located at
the cytoplasmic surface of endoplasmic reticulum, anchored to the membrane by other
enzymes from the cytochrome P450 class (Burbulis & Shirley 1999, Ralston & Yu
2006, Shirley 2001).
Different levels of other flavonoid such as proanthocyanidins and phlobaphenes are
known to relate with grain colour of rice and wheat (Himi et al. 2002, Sweeney et al.
2006). However, whether there is correlation between grain coat colour and ACG
content in grain still needs to be confirmed. Although the alkaline noodles that are made
from the flour of red grained wheat and white grained wheat show differences in b*
value levels which might indicate differences in yellow pigment content in their grains
(Seib et al. 2000), similar levels of apigenin di-C-glycosides were found in the grains of
the red genotype R/W635 and white grained QT7475 (Rathjen 2006).
14
Figure 2.4 The flavonoid metabolic pathway (Asenstorfer et al. 2007, Ayabe & Akashi 2006, Cummins et al. 2006, Lepiniec et al. 2006, Martens & Forkmann 1999, Shirley 2001). The colours indicate branches of the pathway that lead to production of different types of flavonoid compounds. Enzymes that catalyse specific parts of the pathway are shown in blue. Those that function in the first part of the flavonoid pathway: CHS (chalcone synthase) and CHI (chalcone isomerase). Those are proposed to function in flavone-C-diglycoside biosynthesis: F2H (2S-flavanone 2-hydroxylase) and FCGT (flavonoid C-glycosyltranferase), while those that function in flavone biosynthesis: FS1 (flavone synthase 1) and FS2 (flavone synthase 2). Other branches leading to anthocyanin biosynthesis: F3H (flavanone-3β-hydroxylase), DFR (dihydroflavonol-4-reductase), ANS (anthocyanidin synthase), UFGT (UDP glycose:flavonoid-3-O-glycosyltransferase), for flavonol biosynthesis: FLS (flavonol synthase); RT (rhamnosyl transferase), for aurones biosynthesis: AS (aureusidin synthase), for isoflavones biosynthesis: IFS (isoflavones synthase), for proanthocyanidin biosynthesis: LAR (leucoanthocyanidin reductase) and ANR anthocyanidin reductase.
ANS UFGT
Oxidised tannins
Flavonol glycosides
LAR ANR
PPO
RT UFGT
+
naringenin chalcone (chalcone)
CHS
Acetyl-CoA Krebs cycle
3 malonyl-CoA
Phenylpropanoid pathway
4-coumaroyl-CoA
CHI
naringenin (2S-flavanone)
AS aurones
IFS isoflavones
Apigenin (flavone)
FS1/FS2
F2H
hydroxynaringenin (2S-hydroxyflavanone)
Apigenin di-C-glycosides
FCGT
?Ring opening
?isomerisation
anthocyanins
FLS F3H 3-OH-flavanones
(dihydroflavonols) flavonols
DFR
Flavan-3,4-diols (leucoanthocyanidins)
Condensed tannins (proanthocyanidin)
DFR flavan-4-ols phlobaphene
s
15
2.3.2 Pathway leading to apigenin di-C-glycoside biosynthesis in wheat
grain
By comparison with the biosynthesis of anthocyanins, phlobaphenes, and
proanthocyanidins, the part of the flavonoid pathway that leads to the biosynthesis of
ACGs in wheat grain is still only poorly understood. However, based on other studies in
dicotyledonous plants and cereals such as rice and maize, there are several candidate
enzymes that might be involved in ACG biosynthesis (Table 2.2). Two types of flavone
biosynthesis enzymes, flavone synthase 1 (FS1) and flavone synthase 2 (FS2), have
been identified in Petroselinum hortense, rice and Gerbera hybrida (Lee et al. 2008,
Martens & Forkmann 1998, 1999, Martens et al. 2001, Zhang et al. 2007). These two
enzymes have different mechanisms for biosynthesis of flavone from flavanone: FS1
directly converts flavanone into flavone (Martens et al. 2001) while FS2 performs the
conversion via the formation of an intermediate compound, (2S)-hydroxyflavanone
(Akashi et al. 1999).
16
Table 2.2 Enzymes involved in flavone biosynthesis.
Enzymes Un-abbreviated names Plant Source Sequence of the pathway regulated
Reference
flavone synthase I Parsley (Petroselinum hortense ) cv. Italian Giant
Martens et al., 2001
Rice Lee et al., 2008FNSII (CYP93B2) flavone synthase II
(cythochrome 450 93B2)Gerbera hybrida convertion of (2S)-naringenin
to apigenin (flavanones to flavones) through the formation of (2S)-hydroxynaringenin (hydroxyflavanones)
Martens and Forkmann, 1999
MtFNSII-1 Medicago truncatula flavone synthase-1
MtFNSII-2 Medicago truncatula flavone synthase-2flavanone 2-hydroxylase (cythochrome 450 93B1)
Licorice (Glycyrrhiza echinata L.); Fabaceae
Akashi et al., 1998
Snapdragon (Antirrhinum majus )Torenia (Torenia fournieri )
FCGT flavonoid C -glycosyltranferase
Wheat (Triticum aestivum L.)
Cummins et al., 2006
Buck-wheat (Fagopyrum esculentum )
Kerscher and Franz, 1987
addition of 2 glycosyl groups to the hydroxyflavanones, after hemiketal ring opening
FNSI direct convertion of (2S)-naringenin to apigenin (flavanones to flavones)
Medicago truncatula conversion of flavanones to (2S)-hydroxyflavanones
Zhang et al., 2007
F2H (CYP93B1) conversion of flavanones to (2S)-hydroxyflavanones
Akashi et al., 1999
17
Later in the pathway, glycosylation possibly catalysed by a flavonoid-C-
glycosyltransferase (FCGT) is suggested to occur at 6-C and 8-C of apigenin moiety
(Kerscher & Franz 1988). As naringenin, naringenin chalcone or apigenin do not appear
to be substrates for glycosylation (Kerscher & Franz 1988), it is suggested that the ACG
biosynthesis proceeds through a different pathway than those initiated by FS1 and FS2.
The addition of sugar molecules is suggested to take place after a member of
cytochrome P450 superfamily that has very similar amino acid sequences with FS2 of
Gerbera (CYP93B2), CYP93B1 (2S-flavanone 2-hydroxylase (F2H)), which converts
flavanone into hydroxyflavanone by monooxygenation of the flavanones as has been
observed in Glycyrrhiza echinata, Anthirrhinum majus, Torenia fournieri and Medicago
truncatula (Akashi et al. 1998, Zhang et al. 2007).
The involvement of hydroxyflavanone as substrate in biosynthesis of ACG by a
glycosyltransferase was also observed by Cummins et al. (2006). A change in the ACG
content of 7 days old wheat seedlings treated with cloquintocet mexyl herbicide
safeners was reported to be correlated with the increase of C-glycosyltransferase
activity towards 2-hydroxynaringenin. Based on this fact and other previous studies
(Asenstorfer et al. 2006, Brazier-Hicks et al. 2009, Hamilton et al. 2009, Kerscher &
Franz 1987), a novel branch of the flavonoid biosynthetic pathway leading to ACGs in
wheat grain is proposed in Figure 2.5 The initial step involves conversion of 2S-
naringenin flavanone to the hemiketal structure of the flavanone by flavanone 2-
hydroxylase (F2H) (Du et al. 2010, Du et al. 2009). Prior to the glycosylation of 2-
hydroxyflavanone, the hemiketal ring is suggested to open, which activates 6-C and 8-C
to nucleophilic attack (Asenstorfer et al. 2006). This was supported by the identification
of the 2 sets of Wesley-Moser isomers of ACGs in wheat embryo tissues. One set
18
contains arabinose and glucose at 6-C and 8-C position whilst in the other set, glucose is
replaced with galactose. The reactions that follow the C-glycosylation are similar for all
the ACG isomers, with cyclisation, not requiring an enzyme, and water loss involving a
dehydratase (Grotewold et al. 1998, Shirley 2001). The hexose C-glycosylation is
possibly a key reaction determining which diasterioisomer, ACG1 or ACG2, is formed.
Brazier-Hicks et al. (2009) suggested that there was a specific C-glucosyltransferase for
the addition of UDP-glucose to 2S-hydroxynaringenin or its hemiketal in rice.
The glycosyltransferase family has a very diverse protein sequences. Those reported in
plants such as UDP glycose:flavonoid-3-O-glycosyltransferase (UFGTs) are mainly O-
glycosyltransferases. There is considerable information regarding O-glycosylation, but
there is only limited information on the C-glycosides. C-glycosides are found primarily
in grasses but can also be found in some dicots such as Fagopyrum esculentum
(Kerscher & Franz 1987). While C-glycosylation involving a C-glucosyltransferase to
produce ACG1 has been reported (Brazier-Hicks et al. 2009), there is no information on
the C-galactosylation step in ACG2 biosynthesis. Moreover, the genetic regulation of
these two glycosylation events in relation to F2H is also unknown.
19
Figure 2.5 Proposed biosynthesis pathway for the 2 types of apigenin di-C-glycosides
(ACG1 and ACG2) based on reports by Kerscher & Franz (1987), Brazier-Hicks et al.
(2009) and Hamilton et al. (2009).
ACG1 ACG2
20
When this study began in 2008, information on C-glycosyltransferase genes and protein
sequences was only available in the gene bank for actinomycetes
(http://www.ncbi.nlm.nih.gov/sites/entrez?db=protein&cmd= search&term=c-
glycosyltransferase; accessed 18th January 2009). They share 91% similarity with the
plant O-glycosyltransferases, but their acceptor and donor substrates are different
(Hoffmeister et al. 2002). However, the substrate-binding modes are highly conserved
(Mittler et al. 2007). More recently, a C-glycosyltransferase gene and protein sequence
has been reported in rice (Brazier-Hicks et al. 2009).
2.3.3 UDP-sugar recognition by the glycosyltransferases
Generally, glycosyltransferases are highly conserved in their secondary and tertiary
structure (Osmani et al. 2009) and it appears unlikely that a single plant
glycosyltransferase would have broad substrate recognition especially for the sugar
donors (Kubo et al. 2004, Offen et al. 2006, Shao et al. 2005). However, Ono et al.
(2010) reported evidence of a bifunctional UDP-glucose/UDP-galactose: flavonol-3-O-
glucosyltransferase/galacosyltransferase activity in flavonol glycoside biosynthesis.
Since the biosynthesis of the two ACG diasterioisomers is only differentiated by the
hexose C-glycosylation pattern, the variation in contents of individual ACGs and
subsequently the ratio may be an indication of genetic variation in the sugar donor
specificity of the C-hexosyltransferases.
21
2.4 Genetic regulation of flavone biosynthesis in cereal grain
2.4.1 Genetic loci involved in the control of compounds related to the
yellow colour of alkaline noodles
The b* values (yellowness) of noodles and the QTL/molecular markers associated with
genetic variation have been mapped on chromosome arms 2DL, 2DS, 3AS, 3BL 4BS,
5BL, 7AL, and 7BL (Elouafi et al. 2001, Kuchel et al. 2006, Mares & Campbell 2001,
Parker et al. 1998, Parker & Langridge 2000, Patil et al. 2008, Pozniak et al. 2007).
QTL on the group 3 and 7 chromosomes are known to relate with xanthophyll
biosynthesis (Mares & Campbell 2001, Parker et al. 1998). A microsatelite (SSR,
simple sequence repeat) marker, Xgwm344 on chromosome 7BL was linked to QTL for
yellowness of noodles in durum wheat and bread wheat (Elouafi et al. 2001, Kuchel et
al. 2006) and xanthophyll content (Harker et al. 2001). Psy1-1, a key gene involved in
xanthophyll biosynthesis was mapped in the QTL region on chromosome 7A and 7B
(Kuchel et al. 2006, Mares & Mrva 2001, Pozniak et al. 2007). Similarly, the QTL
located on the group 3 chromosomes contains another key gene, Є-cyclase (Є-LCY), in
the xanthophyll biosynthesis pathway (Howitt et al. 2009).
In a preliminary study, Mares and Wilsmore (unpublished data) identified a QTL on
chromosome 7B using the map reported by Chalmers et al. (2001) that was associated
with variation for the content of ACG1 and ACG2, the ratio of ACG1 and ACG2 and
the total amount of both ACGs in grain in a Sunco x Tasman doubled haploid
population. Statistical analysis showed a highly significant correlation between the ratio
of ACG1/ACG2 and SSR marker Xwmc76 that explained 83% of the variation in the
population (Table 2.3, Figure 2.6). A fine map of this QTL needs to be generated to
further explore these possibilities.
22
Table 2.3 DNA markers on chromosome 7B that were linked with ratio, ACG1/ACG2
in grain of Sunco x Tasman population (Mares and Wilsmore, unpublished data).
A NOTE:
This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.
23
Figure 2.6 Location of DNA markers on chromosome 7B of Sunco x Tasman
(GrainGenes, accessed 22 September 2008).
2.4.2 Transcriptional regulation of flavonoid biosynthesis
Differential regulation of expression of sets of structural genes involved in different
branches of the flavonoid metabolic pathway has been observed in a number of plants
(Quattrocchio et al. 2006). However, functional redundancy was observed in the types
of transcription factor proteins involved. Lepiniec et al. (2006) suggested that there was
separate regulation of different sections of the pathway i.e. early biosynthetic genes
A NOTE:
This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.
24
(EBG) and late biosynthetic genes (LBG) in Arabidopsis thaliana. Recent studies with
different dicotyledonous plants has shown that the division into EBG and LBG varies
for different tissues and plants (Deluc et al. 2008, Dubos et al. 2008, Gonzalez et al.
2008). In maize, all of the structural genes of the flavonoid metabolic pathway are
induced simultaneously in coordination by several sets of transcription factors
(Grotewold et al. 1998).
Similar communication and cooperation between transcription factors has been
suggested in Arabidopsis and maize (Zhu 2006). Regulation by transcription factor
interaction may be positive, resulting in the activation of structural genes and the
production of certain group of compound at the end of the branch, or negative,
resulting in the suppression of gene expression (Quattrocchio et al. 2006). The
correlation between QTL or the gene for the expression of these transcription factor
genes and the accumulation of structural gene transcripts and products have been
previously studied in various plants including hexaploid wheat (Himi & Noda 2006,
Khlestkina et al. 2008, Lagudah et al. 2001).
2.4.3 Transcription factors controlling flavonoid biosynthesis in cereal
grain
There are two families of transcription factor proteins that are known to regulate the
flavonoid biosynthetic pathway, R3R2-myb and bHLH. In Arabidopsis, interactions
between these two families of transcription factors together with a WD40 repeat protein
have been reported to lead to anthocyanin and proanthocyanidin biosynthesis, while the
activity of R2R3-myb alone leads to the induction of flavonol and phlobaphene
biosynthesis genes (Figure 2.7) (Quattrocchio et al. 2006). Slightly different regulation
25
is shown in maize where interaction between C1 and R, members of R2R3-myb and
bHLH transcription factor respectively, only has been shown to result in the activation
of anthocyanin, proanthocyanidin and flavonol glycoside biosynthetic genes (Goff et al.
1992). The activity of the myb transcription factor P alone results in the production of
C-glycosyl flavones and phlobaphenes (Grotewold et al. 1998).
According to Himi et al. (2005 and 2011), R genes for grain coat colour code for myb
transcription factors that upregulate chalcone synthase (CHS), chalcone isomerase
(CHI), flavanone 3-hydroxylase (F3H), and dihydroflavonol 4-reductase (DFR). Whilst
in red-grained wheats the R genes are associated with dormancy, it appears that
expression of a dormant phenotype requires at least one other gene (Mares et al. 2005).
Many red-grained wheat genotypes are non-dormant.
A study in rice suggested that the R locus in wheat might be orthologous with the Rd
gene in rice (Sweeney et al. 2006). Both are located at homologous positions on
chromosome 3 and 1 of wheat and rice respectively. However, the Rd locus of rice does
not have phenotype when it is present alone (Sweeney et al. 2006) and encodes DFR to
produce red seed colour in the presence of Rc gene (Furukawa et al. 2006). Moreover, a
recent study by Balyan et al. (2008) argued that Rd of Rice was not orthologous with
the R gene of wheat. The wheat genomic region containing the R gene appeared to be
approximately 16Mb distal to the region containing the wheat homologue of the Rd
locus of rice.
26
Figure 2.7 Activation of structural genes of flavonoid biosynthesis by transcription
factors (Quattrocchio et al. 2006). A) The activity of R2R3-myb alone leads to the
induction of flavonol and phlobaphene biosynthesis genes. B) Interaction between
R2R3-myb, bHLH, and WD40 repeats (WDR) leads to anthocyanin and proanthocyanin
biosynthesis.
The Rc gene, a bHLH transcription factor gene of proanthocyanidin biosynthesis on
chromosome 7 of rice, encodes brown pericarp and seed coat when it is present without
Rd (Sweeney et al. 2006). The study in wheat reported that the Rc loci for red
pigmentation in coleoptiles is located on chromosomes 7A, 7B, and 7D (Khlestkina et
al. 2002). They function as myb transcription factors for the expression of F3H, DFR,
ANS (anthocyanidin synthase), and UFGT (UDPG flavonol 3-O-glucosyl transferase)
27
genes of flavonoid pathway that lead to anthocyanin biosynthesis (Ahmed et al. 2006,
Himi et al. 2005, Khlestkina et al. 2008).
The R and Rc loci may regulate flavonoid metabolic pathway genes leading to
anthocyanin biosynthesis in wheat similar to Arabidopsis thaliana, i.e. the R gene might
be the transcription factor for genes in the early part of metabolic pathway (EBG) while
Rc seems to be the transcription factor for the LBG. Other transcription factors such as
bHLH and WDR40 might also interact with the myb transcription factor in regulating
FCG biosynthesis. However, it perhaps more likely that the regulation of ACG
biosynthesis in wheat is similar to that of maize, where a myb transcription factor
coordinates the flavone biosynthesis gene expression. In this model, the R gene or other
myb transcription factor genes might coordinately control the expression of flavone
biosynthesis genes in wheat from EBG to the LBG.
2.5 Wheat genomics for studying genetic regulation of flavone-di-C-
glycoside biosynthesis
2.5.1 Organization of the wheat genome and wheat genomic information
The wheat species, Triticum aestivum L., commonly used for yellow alkaline noodles
has the largest genome of all crop species, over 16,000 megabases (Gill et al. 2004)
with a complex genome (Langridge et al. 2001). It is an allohexaploid species with 3
different genomes (A, B, D) originating from different ancestors (Lupton 1987). Within
each genome, the genetic information is packed into 7 pairs of chromosomes (2n = 6x =
42) (Francki & Appels 2002). The genes in bread wheat are unevenly distributed along
the chromosome interspersed with repetitive non-coding sequences (Flavell & Smith
1976). Approximately, 80% of the genome is occupied by repetitive (non-coding)
28
sequences and the rest consists of low copy number genes (Francki & Appels 2002).
Akhunov et al. (2003) suggested that the genes are clustered in gene-rich islands that
are dispersed throughout the chromosome length. Genome rearrangements and deletions
that occurred during the species evolution without major detrimental effect on the plant
have added greater complexity to the genome and therefore its study (Devos & Gale
2000, Langridge et al. 2001, Salina et al. 2006). Some genomic information (listed in
Table 2.4) is available publicly online and can be useful for comparative genomic
studies of plants.
Many studies have been performed on the organization of wheat genomes. Recently, the
genomes of wheat have been fully sequenced by whole genome shotgun sequencing
method (Brenchley et al. 2012) and the sequences have been made publicly available
(www.cerealdb.uk.net). However, the sequences have not yet been fully annotated and
assembled into chromosomes.
29
Table 2.4 Online Resources for comparative genomic study of plants.
30
2.5.2 Methods for studying regulation of gene expression in wheat
2.5.2.1 Reverse and forward genetic approaches for studying regulation of
gene expression in wheat
Two approaches are widely used in studying gene function in plants, forward and
reverse genetics (Peters et al. 2003). In forward genetics, the study of genetic regulation
involves first observing the phenotype followed by identification of genes that are
responsible for the traits (Alonso & Ecker 2006). In contrast, in reverse genetics, the
study involves identifying gene sequences in a database followed by induced mutation
or silencing of the gene and subsequently observation of the resulting phenotype.
The large size of wheat genome, high incident of repetitive non-coding regions and the
existence of three genomes of the wheat discourage the application of reverse genetics
in wheat (Stein & Graner 2004). As the gene sequences in plant species are generally
conserved (Lagudah et al. 2001), the function of sequences from model plants or other
cereals can be applied in wheat (Marshall et al. 2001). However, the homology and
synteny between wheat and other cereal or model plant sequences is often only useful as
a guide. The gene sequences and their order within the genome between wheat and
other cereals may be very similar, but other features of the genome such as regions
between genes and the non-coding sequences can be significantly different (Francki &
Appels 2002). The occurrence of numerous translocation, inversion, insertion and
deletion events during evolution may also hinder the discovery of homologous gene
sequences (Francki & Appels 2002, Gill et al. 2004, Lagudah et al. 2001). Depending
on the level of genetic relatedness, comparison of genomes should also take into
account the similarity in gene products and physiological features associated with their
growth and development (Lagudah et al. 2001). Deducing the gene homology through
31
similarity of gene products might be more suitable in comparing wheat and model plant
genomes than direct gene sequence alignment (Lagudah et al. 2001).
Unfortunately the application of reverse genetics in wheat is not always straight forward
and several important molecular techniques such as southern blot and genetic
transformation are difficult to apply, with significantly higher rates of failure in wheat
than in other plants (Langridge et al. 2001). The presence of the three different genomes
of wheat means three sets of bands will usually appear in many molecular marker
analyses particularly restriction fragment length polymorphism (RFLP). The
identification of gene sequences in wheat mainly depends on the map based cloning
approach of forward genetics (Francki & Appels 2002). Initial work to identify wheat
transcription factor genes are mainly performed by fine mapping, especially when the
previous sequence information is unavailable (Stein & Graner 2004). Transcript
analysis can be performed following the fine mapping by reverse transcription
polymerase chain reactions (RT-PCR) based techniques (Ahmed et al. 2006, Himi et al.
2005, Himi & Noda 2006) after the candidate gene sequences are successfully
identified.
2.5.2.2 Identification of transcription factor genes through genetic mapping
and positional cloning
Genetic mapping and positional cloning have been used to isolate genes from complex
genomes. Co-localization of genes on genetic and physical maps is used to identify
DNA sequences by aligning the physical and genetic maps and placing the genetic
markers on the physical map and the DNA fragments on the genetic map to validate
both maps (Goyal et al. 2005, Liu 1998). The order of the linked genes in both maps is
32
usually conserved and the genes can be ordered precisely on the physical map (Stein &
Graner 2004).
A wide range of resources are available for genetic mapping. Nullisomic-tetrasomic
series as well as ditelosomic lines of wheat variety Chinese Spring are available to
locate genes controlling agronomically important traits to specific chromosome or
chromosome arms respectively (Lupton 1987). Moreover, the availability of molecular
markers that have been placed into either genetic or physical maps of various wheat
breeding populations make it possible to perform linkage analysis at high resolution
(fine mapping) (Langridge et al. 2001). Good levels of polymorphism have been shown
in the application of SSR markers within Australian germplasm (Chalmers et al. 2001,
Harker et al. 2001, Parker et al. 1998) although polymorphisms are more difficult to
identify in wheat than in other species (Langridge et al. 2001). In a study by Harker et
al. (2001), around 148 polymorphic SSR markers were identified in a Sunco × Tasman
doubled haploid population with 93% loci located in linkage groups. Chalmers et al.
(2001) reported 11 polymorphic DNA markers, but few SSR markers, in the region of
chromosome 7B in Sunco x Tasman where the QTL for ACG1/ACG2 ratio of ACGs is
located (Mares and Willsmore, Unpublished). However, more recent publications
involving other wheat populations suggest that there are many SSR markers on the short
arm of 7B chromosome that could be tested (Ganal & Röder 2007). Information on the
various aneuploid and chromosomal mutant lines of wheat that can be used for
assigning SSR markers to linkage groups and for physical mapping is available on the
GrainGenes website (Langridge et al. 2001).
33
Some loci on 7BS were observed to be homologous to those on 5BL and 5DL instead of
7AS and 7DS (Nelson et al. 1995) and may be useful for saturating the QTL region on
7BS. The translocation, inversion and re-arrangements between 4A, 5A, and 7B
chromosomes during the polyploidization in hexaploid wheat evolution impacted on the
recombination in these chromosomes (Devos et al. 1995, Salina et al. 2006). The
genetic map and physical map of group 7 chromosomes of hexaploid wheat was
reported to be collinear (Hohmann et al. 1994), as many as 54 homologous loci have
been located on chromosomes 7A, 7B, and 7D with almost identical linear order of the
molecular markers between the 3 chromosomes. However, the physical distant was not
correlated with the genetic distant and some distortion in distal regions of chromosomes
were identified.
The identification of QTL may require the development of a new population from
parents with more extreme phenotype, but for which a map is not available. Diversity
arrays technology (DArT) that types hundreds to thousands of genomic loci in parallel
can be applied to provide such a map (Semagn et al. 2006). For routine genotyping of
hexaploid wheat, the maps generated by this technology provide preliminary genome
coverage with information and quality comparable to combined SSR/RFLP/AFLP
(amplified fragment length polymorphism) maps (Akbari et al. 2006).
2.5.2.3 Availability of resources for synteny analysis to determine
transcription factor gene sequences
Whilst a fully annotated wheat genome is not yet available , resources such as the BAC
library and EST sequence database of wheat may be used to construct DNA sequences
containing the genes of interest (Gill et al. 2004, Moolhuijzen et al. 2007). The
34
information on the macrosatellite and SNP marker based deletion bin system for
establishing relastionships between physical and genetic maps are also publicly
available (Akhunov et al. 2010, Sourdille et al. 2004b). The availability of full sequence
information of syntenic chromosomes in rice and Brachypodium distachyon assisted in
the organisation of the contigs and establishing the relationship between the physical
map and the fine genetic map of a chromosome. In this way, the physical map of group
3 chromosome of wheat and the respective genetic map has been developed (Dilbirligi
et al. 2006, Fleury et al. 2010, Paux et al. 2008, Stein 2007).
So far, the BAC library of bread wheat is available mainly for the A and D genomes,
(http://wheatdb.ucdavis.edu:8080/wheatdb/) (Lijavetzky et al. 1999, Shen et al. 2005,
Stein 2007) that were sequenced from the diploid species Triticum uratu and Aegilops
tauschii. The relationship between these diploid genomes and the hexaploid bread
wheat genomes have also been established through the genetic maps (Boyko et al. 2002,
Gill 1991). For the B genome, a BAC library of the S-genome of Aegilops speltoides
that has been reported to be closely related to the B genome of hexaploid bread wheat,
is also available (Akhunov et al. 2005). In addition, the BAC library for the B genome
is also available for the tetraploid wheat relative, Triticum turgidum spp. durum (Cenci
et al. 2003). This BAC library should also be useful for a comparative genomic study,
as the B-genome chromosomes of this species and bread wheat are >99% identical
(Kubalakova et al. 2005).
The wheat EST database contains the most current wheat genomic information
available. In 2004, more than 500,000 sequences were stored in the wheat database,
representing around 60% of the wheat genes (Gill et al. 2004). In 2009, this had
35
increased to more than 1,000,000 sequences for wheat and closely related species stored
in various EST databases (http://www.ncbi.nlm.nih.gov/dbEST/dbEST_summary.html;
verified 6 Jan 2009; http://www.plexdb.org/). Furthermore, thousands of ESTs have
been mapped to wheat genetic and physical maps as single genes and used to reveal
wheat-rice genome colinearity (Adom et al. 2003, Stein 2007). In addition, database and
other resources for mapping the EST sequences into the deletion bin map have been
developed (Lazo et al. 2004 ). A chromosome bin map for group 7 homologous
chromosomes with 2148 EST was reported (Hossain et al. 2004 ). Similar information
was also reported for 1918 EST loci in wheat homologous chromosome 4.
Besides the wheat EST database, the complete genome sequence of rice is also available
for analysing synteny (Salse et al. 2008). DNA marker distributions along physical
chromosome maps of these two cereals are generally collinear (Dunford et al. 1995).
The distance may be different, but the order of the markers and genome structure are
generally conserved (Kurata et al. 1994, Moore 1995). From the distribution of EST
sequences in physical maps of wheat deletion lines and their segregating populations,
group 7 wheat chromosomes are known to be collinear with a combination of several
segments of rice chromosomes. The short arms of wheat chromosome 7 are matched
with short arms of rice chromosome 6 and long arms of chromosome 8 while the long
arms of wheat chromosome 7 are matched with the long arms of rice chromosome 6 and
short arms of chromosome 8 (Rota & Sorrells 2004).
In addition to the rice full genome sequence, other sources for genome comparison are
also available. The genome of a new model plant for temperate grasses and cereals,
Brachypodium, should be useful in bridging the gaps between wheat and rice (Hasterok
36
et al. 2006). The BAC library of this species has been available for synteny analysis
since early 2009. Moreover, a BAC „landing‟ method for comparative genome
alignment between cool season grasses such as wheat and Brachypodium has also been
published (Jenkins & Hasterok 2007).
The assembly of gene sequences by genome comparison and sequence alignment results
in putative sequences of interest (or contigs) (Gupta et al. 2008). Unfortunately, ESTs
for genes with low expression might not be detected whilst transposable elements and
alternatively spliced gene sequences might be misidentified as multiple unigenes (Stein
2007). In addition, small translocations, deletions, inversions, and duplications often
violate colinearity and complicate the synteny analysis (Gill et al. 2004). After the
putative gene sequences are obtained, confirmation of their function is performed
through gene transcript analysis (Leader 2005).
2.5.2.4 Transcript analysis of wheat genes
In previous studies (Ahmed et al. 2006, Himi et al. 2005, Himi & Noda 2004,
Khlestkina et al. 2008), the expression profiles of transcription factor genes have been
shown to be correlated to the expression of biosynthetic genes. The transcript analysis is
performed by Reverse Transcript PCR techniques. When the information on the
structural gene sequences is unavailable for the plant under study, a bioinformatics
analysis is first performed to identify these sequences in the EST library by using
available sequences as references. This can be done before correlating the expression
level of the transcription factor loci resulting from fine mapping to the structural gene
transcripts and to the metabolic content (Lagudah et al. 2001).
37
2.6 Conclusion
As the yellow colour of yellow alkaline noodles (YAN) influences their market value,
improvement of the natural yellow colour compounds in wheat grain and flour is
important. Apigenin di-C-glycosides (ACGs) in wheat grain make a significant
contribution to the yellow colour YAN. It is therefore desirable to improve the ACG
content in wheat grain, but unfortunately there is only limited information available on
the genetic variation for ACG content in Australian or other wheat cultivars. Similarly,
whether existing populations are suitable for further genetic mapping study remains to
be determined and there is no information on the enzymes and the genes involved in the
critical part of flavonoid pathway that leads to ACG biosynthesis in wheat grain.
However, there is information on the enzymes that code for flavone biosynthesis in
wheat and related plants and transcriptional regulation of the general flavonoid pathway
that can be used as a starting point for studying biosynthesis of ACG.
QTL and SSR markers linked to variation in ACG composition in a specific wheat
population (Sunco x Tasman) have been identified. Fine mapping of this locus and a
comparative genomic study with the aid of EST and BAC libraries available for wheat
and other cereals are required to identify the candidate gene sequences involved in ACG
biosynthesis. These sequences could be the structural gene or a transcription factor
gene(s) involved in ACG biosynthesis. A correlation between the expression of these
candidate sequences and ACG synthesis during grain development would verify their
importance to the ACG pathway.
Potentially, there are myb, bHLH and WDR40 transcription factors that regulate other
branches of the flavonoid pathway, could regulate ACG biosynthesis as well. The R
38
genes that encode myb transcription factors in wheat and orthologues in other cereals
including rice and maize that are important in regulating large portions of the flavonoid
pathway might also be involved in regulating ACG synthesis in wheat grain. A
sequence analysis followed by transcript analysis to correlate the expression of these
transcription factor genes with the structural gene transcripts, and the ACG
concentration would give information regarding their importance to ACG biosynthesis.
2.7 Research questions
The overall aims of this project are to quantify the contribution of apigenin di-C-
glycosides to the colour of YAN and to investigate the genetic regulation of their
biosynthesis in wheat grain.
2.8 Research aims
The specific aims of this project will be:
to survey the genetic variation in grain ACG content and composition within
Australian bread wheat cultivars.
to determine the quantitative role of ACG in the yellow colour of YAN
to locate and to validate the QTL associated with ACG content, concentration
and composition in bread wheat grain.
to fine map the highly significant QTL region on 7BS.
Survey genes likely to be located in the fine-mapped region on chromosome 7B
for candidate genes involved in determining ACG composition
39
2.9 Significance/contribution to the discipline
This research will provide new information on the role of apigenin di-C-glycosides in
the colour of YAN and the genetic control of the biosynthesis of these compounds in
wheat grain. Moreover, the research may also show whether all the genes involved in
flavone biosynthesis in wheat grain are co-ordinately regulated by a set of transcription
factors, or whether there are separate regulators for early and later stages of the
pathway.
40
Chapter III: General Materials and Methods
3.1 Introduction
In this chapter, the background on the materials and methods that have been used in this
thesis are outlined and explained. The details on the use of these materials and methods
for specific work have been described in the relevant chapter.
3.2 Plant Materials
3.2.1 Genetic resources for experiment 1 (Chapter IV): Survey of genetic
variation in ACG content and composition
Seventy bread wheat (Triticum aestivum L.) genotypes were sourced primarily from
Australian breeding programs, but also included a small number of varieties of
miscellaneous origin. The complete list of these cultivars is in supplemental material
4.1. Forty four of these cultivars were released by various Australian breeding program
in 5 different states Queensland, New South Wales, Victoria, South Australia and
Western Australia. Twenty six of the cultivars from miscellaneous sources were
obtained either from The University of Adelaide pre-breeding program (10 cultivars), 2
from Leslie Research Center in Queensland, 2 from South Africa, 5 from China, 1 from
Japan whilst 2 cultivars and 4 synthetic derived hexaploid wheats originated from
Mexico. In 2009, 29 genotypes from the Australian breeding program that cover the
range in ACG content were selected for a G X E experiment.
The diploid, tetraploid, and hexaploid relatives of breadwheat: accessions of Triticum
monococcum (AmAm), Triticum uratu (AA), Aegilops tauschii (DD), Aegilops
speltoides (SS), Triticum dicoccum (AABB), Triticum polonicum (AABB), Triticum
41
turgidum (AABB), Triticum diccoides (AABB), Triticum carthlicum (AABB), Triticum
durum (AABB), and Triticum spelta (AABBDD) were obtained from the Australian
Winter Cereals Collection, Tamworth; while 5 Triticum durum cultivars were obtained
from Australian breeding program in NSW (4) and South Australia (1) (supplemental
material 4.1).
Aneuploid lines: The full set of 42 nullisomic-tetrasomic lines of Chinese Spring (Sears
1981) were obtained from Ms. Margie Pallotta of the Australian Centre for Plant
Functional Genomics, The University of Adelaide. A set of Chinese Spring/Triticum
spelta chromosome substitution lines (21 lines where each Chinese Spring chromosome
in turn was substituted with the homologous T. spelta chromosome) was sourced from
the John Innes Research Centre, UK.
3.2.2 Genetic resources for experiment 2 (Chapter V): Quantitative
assessment of content and composition of the ACGs and their
contribution to YAN colour in comparison to that of lutein
Twenty eight cultivars of Australian commercial bread wheat (Triticum aestivum L.)
representing all the wheat production zones in Australia, that were grown in a field trial
at Turretfield in South Australia in 2005, were used both for analyses of grain ACG
content and composition as well as for preparation of flour using a Quadrumat Junior
Mill. Ten were re-sown in 2009 to provide sufficient sample size for Bühler milling.
Sunvale (Australian Premium Hard quality in NSW and Queensland region and
Australian Hard quality in other states including South Australia) flour was used as the
base for construction of a standard curve quantifying the effect of addition of different
42
amounts of rutin on YAN colour. Suneca (Australian Premium Hard quality in NSW
and Queensland region and Australian General Purpose quality in other states including
South Australia) was used as a control to monitor the milling process.
3.2.3 Population for experiment 3 (Chapter VI): Genetic control of the
ACG content and composition in bread wheat grain
3.2.3.1 Parents of Australian doubled haploid populations
Initially, parents of 7 existing bread wheat doubled haploid populations, Sunco/Tasman,
Sunco/Aroona, Avocet/Sunvale, Avocet/Angus, Avocet/Sunfield, Sunvale/Sunfield, and
Cranbook/Halberd were grown in Turretfield, South Australia in 2005. Their grains
were analysed and compared for ACG content and composition.v
Of these, Sunco/Tasman was chosen for further study since the parents were shown to
vary significantly for ACG composition, although not significantly for total ACG
content, (Supplemental materials 3.1, 3.2, and 3.3) and because a genetic map was
already available (Kammholz et al. 2001). This doubled haploid population has also
been widely used for mapping other traits related to noodle colour (Mares and
Campbell, 2001).
3.2.3.2 Sunco/Tasman doubled haploid population used in the QTL
mapping
Whilst there were 269 doubled haploid lines generated from the cross, Sunco/Tasman,
the lines used as the mapping population represent the first 180 transferred from culture
(Kammholz et al. 2001). Due to high segregation distortion in the molecular marker
data (Chalmers et al. 2001, Kammholz et al. 2001), this population has been sub-
43
sampled in the further studies examining the segregation of various major genes. In
2008, the genotype (308 markers) and phenotype data used in these studies were made
available in MapManager database. These data were provided by Dr. Anke Lehmensiek
and Dr. Kerrie Willsmore, and converted into excel spread sheet by Dr. Greg Lott. As
many as 203 of the original Sunco/Tasman doubled haploid population were
phenotyped for ACG content, ACG composition, 100 grain weight, ACG1 content,
ACG2 content, total ACG per gram and total ACG per grain in 2005 by Mares and
Asenstorfer (unpublished data). Only 147 lines from these 2 data sets had matching
identification. In 2010, another set of genotyping data of 178 lines with 361 markers
was obtained from Professor Rudi Appels, Murdoch University, and Prof. Mrinal Bhave
and Dr. Huimei Wu (Swinburne University of Technology). Markers on chromosome
1A and 7B were used to compare this data set with the 2008 genotyping data
(Lehmensiek, Willsmore and Lott). A new set of Sunco x Tasman doubled haploid
population data was compiled with 153 lines and 361 markers, to validate the
preliminary QTL mapping of ACG traits performed by Mares and Willsmore
(Unpublished data).
In 1999, seed of 271 doubled haploid lines, provided by Dr S. Kammholz, Leslie
Research Centre, Toowoomba, Queensland, Australia, was increased in a field trial at
Narrabri in New South Wales, Australia. Sunco and Tasman parent lines were planted
alternately every 20th plot within the trial (Supplemental material 3.4A and 3.4B). The
grains of these lines were stored at -200C until required for this project.
Four SSR markers: wmc76, gwm400, gwm573 and wmc364 on 7BS that flanked the
QTL region for ACG1, ACG2, and ACG1/ACG2 ratio were used to compare this
44
population with the previous mapping data (Lehmensiek et. al in 2008, Bhave et. al in
2010, Mares and Asenstorfer unpublished data). The multiplex PCR results for the other
markers, gwm400 and wmc76 were confirmed by the second PCR and gel
electrophoresis visualisation. The result for wmc364 was confirmed by the second data
set from Bhave et. al in 2010.
The distribution of the new phenotypic data for the first set of population lines (163
lines) was compared with the additional lines of the population from as a second group
(108 lines). Four lines of the final compilation of the genotypic and phenotypic data set
did not have phenotypic data because the grain was unavailable. The frequencies of
ACG1/ACG2 ratio data of these two groups were distributed with the first group have
slightly higher ratio range than the second group (Supplemental materials 3.5). The low
ratio data distributed similarly, but the high ratio data were slightly higher for the first
group than the second group. The differences in the trait distribution may be a result of
more than one F1 used in generating the mapping population (Kammholz et al. 2001).
3.2.3.3 Other genetic stocks used in marker analysis
A panel of Sunco/Tasman doubled haploid lines were chosen for polymorphism test of
the SSR markers. This panel consisted of 10 lines with ratio similar to Sunco (high
ratio) and another 10 lines with ratio similar to Tasman (low ratio). Two pairs of lines
of these population parents were also included in the test. The nullisomic-tetrasomic
lines of Chinese Spring group 7 chromosomes (section 3.2.2) and ditelosomic lines
group 7 were used to confirm the chromosome arm location and designing the SNP
markers. The ditelosomic lines were obtained from Prof. R. Mc Intosh, University of
Sydney, New South Wales, Australia.
45
3.3 Location, time, and condition of planting of the genetic resources
Locations and time of planting of the genetic resources used in this thesis is presented in
Table 3.1. For those grown in the glasshouse, the seeds were germinated on filter paper
in a petri disk moistened by 4 mL water and stored in the dark at room temperature for
3-4 days. The seedlings were then transplanted into coconut fibre potting mix and keep
in the glasshouse with controlled environment. For those grown in the field, the seeds
were directly sown in the soil.
Table 3.1 Locations and time of planting of the genetic resources used in this thesis.
Experiments Plant Materials Location of planting Year Survey of genetic variation
70 bread wheat cultivars
Field, Turretfield, South Australia in 2005
2005
35 relative species of bread wheat
Glasshouse, Waite Campus of the University of Adelaide
2009
Chromosome modification and substitution lines
Glasshouse, Waite Campus of the University of Adelaide
2009
29 lines for G X E experiment
Field, Turretfield, South Australia in 2005 and Waite Campus of the University of Adelaide
2009
F1 generations Glasshouse, Waite Campus of the University of Adelaide
2009
Quantification of ACG contribution to YAN colour
28 cultivars for Udy cyclone Mill and Quadrumat Junior Milling
Field, Turretfield, South Australia in 2005
2005
10 cultivars for Bühler milling
Field, Turretfield, South Australia in 2005
2009
QTL analysis and fine mapping
Sunco x Tasman doubled haploid population
Glasshouse, Plant Genomic Center, Waite Campus of the University of Adelaide
2009
Nullisomic-tetrasomic lines and ditelosomic lines of group 7
Glasshouse, Waite Campus of the University of Adelaide
2009
46
3.4 Phenotyping
3.4.1 Data collection
3.4.1.1 ACG analysis
Methods for extraction and quantification of ACGs were as reported by Asenstorfer at
al. (2007), Asenstorfer et al. (2006) and Ingram (2006) with minor modifications.
Initially, the grain weights were recorded. The grains were ground to a fine meal using a
3 M ESPE Rotomix, and 0.1 g of the whole meal mixed with 1.8 mL of 0.1 M
hydroxylamine (Sigma, St Louis, USA) pH 7.0. Subsequently, each sample was spiked
with 50 L of vanillin standard (Sigma, St. Louis, USA) and mixed for 24 hours prior to
centrifugation at 2100 g for 10 minutes. The supernatant was then loaded onto a reverse
phase SPE (StrataTM -X33m C18 polymorphic sorbent, Phenomenex, Torrance, CA,
USA) column preconditioned with methanol and water. ACGs were eluted from the
column using methanol (technical grade, Crown Scientific) the eluate spiked with 50 L
rutin (Sigma, St. Louis. USA) and then vacuum concentrated. The residue was re-
suspended in 250 L of 50% methanol.
The HPLC analysis was performed on a Hewlett-Packard HPLC 1100 instrument
equipped with an autosampler, column heater and diode array detector. Separation was
achieved on a C18 column (Platinum EPS 100A 3 µ 53x7 mm; Alltech, Illinois, USA).
Two solvents, A (HCOOH (Merck KGaA, Darmstaat, Germany)/H2O (1:99 v/v)) and B
(HCOOH (Merck KGaA, Darmstaat, Germany)/CH3CN (Gradient 240nm/far uv, HPLC
grade, Scharlau, Sentmenat, Spain)/MeOH (Isocratic HPLC grade, Scharlau, Sentmenat,
Spain) (1:4:95 v/v/v) were used as eluents, with elution at a flow rate of 0.65 mL/min
according to the following elution profile: 0-3 min, isocratic B; 3-8 min gradient 10%B
to 24% B; 8-11 min, isocratic 24% B; 11-18 min, gradient 24% B to 34% B; 18-28 min,
47
gradient 34% B to 44% B; 28-35 min gradient 44% B to 65% B; 35-40 min, gradient
65% B to 95% B; 40-55 min, isocratic 95% B; 55-60 min, gradient 95% B to 10% B;
60-70 min isocratic 10% B. Analytical wavelengths, UV 340 nm, was used for detection
and quantification of the ACG.
This method was used in all ACG analysis in this study, except for analysis of ACG
content in flour, which will be explained in the relevant chapter (Chapter V).
3.4.1.2 The Use of Internal and external standard solutions in ACG
Analyses
3.4.1.2.1 The use of vanillin internal standard in ACG analyses
Vanillin was used because it is not present in wheat grain, it elutes in a region of the
chromatogram that is free of other constituents, and is stable under the sample
preparation and HPLC conditions used in this study. Vanillin was added after extractant
and sample were mixed and used primarily to monitor any losses during the reverse
phase SPE step and extract drying. The recovery was consistent throughout and very
similar to the recovery of pure vanillin on its own. In rare cases where it was not, the
samples were repeated.
Two replicates of controls contained blank samples (without whole meal materials)
were spiked with 50 L pure vanillin standards (2.5 mg/mL stock solution, Sigma, St.
Louis, USA). The analytical 280nm UV wavelength detected the peak of vanillin
standard at 8.322 minutes. The areas of the vanillin peaks obtained from these controls
and from the samples were then compared and calculated as in section 3.4.2.1 to get the
vanillin corrected area values.
48
3.4.1.2.2 The used of rutin internal standard
Rutin (50 L, from 0.5mg/mL stock solution, Sigma, St. Louis. USA) were used to
spike the ACG samples eluted from the SPE column using methanol prior vacuum
concentrating. Two controls of pure rutin standard at similar concentrations were also
prepared. The analytical 340nm UV wavelength detected the peak of rutin standard in
these samples and controls at 16.492 minutes. The areas of the rutin peaks obtained
from every sample and from each sets of HPLC measurments were compared. In rare
cases where differences were occured, the samples were repeated, and if the differences
stayed, the rutin area values were used to correct the differences between these sets of
measurements.
3.4.1.2.3 The use of rutin external standard
A series of rutin dilutions (10 to 1000 times) were prepared from 1 mg/mL of rutin
stock solution in 50% methanol (isocratic HPLC grade, Scharlau, Sentmenat, Spain).
The areas of these rutin dilutions were measured by HPLC at 340nm UV wavelength.
To construct the standard curve, these areas were plotted as abscissa againts
concentrations of rutin as ordinate in Microsoft Excell worksheet (version 2007). A
trendline and the coefficient of this standard curve were regenerated to calculate the
rutin equivalent of ACG content in the samples as in section 3.4.2.1.
3.4.1.3 Hundred grain weight
The 100 Grains were counted using a seed counter (CONTADOR, Pfeuffer GmbH) and
the weight was measured using an analytical balance.
49
3.4.2 Data Analysis
3.4.2.1 Calculations of ACG traits
Seven ACG content and composition traits were calculated from the raw data of ACG1
and ACG2 obtained from HPLC analysis: concentration and content per grain for
ACG1, ACG2 and total content of and ACG1/ACG2 ratio.
Firstly, the vanillin corrected areas were calculated as follows:
area of pure vanilin std X Area of ACG1 or ACG2 area of vanilin std in each samples then, the volume corrected area were calculated as follows:
Vanilin corrected area (for each ACG1 or ACG2) X final dilution volume (L) 1000 The concentrations of each ACG1 and ACG2 content per gram sample (g/gram) were calculated as follows:
Volume corrected area X 1000 . standard curves coefficient sample weight (g) while each ACG1 and ACG2 content in a grain (g/grain) were calculated as follows: Concentration of ACG1 (or ACG2) in g/g sample X weight (g) per 1 grain The total content of ACGs was calculated as:
ACG1 content + ACG2 content and the ACG1/ACG2 ratio were calculated as:
ACG1 content ACG2 content
50
3.4.2.2 Statistical Analysis
All statistical analyses were performed in GENSTAT software (version 14; VSN
International, Hemel Hempstead, UK). Details of these analyses were explained in
relevant chapters.
51
Title of Thesis: Genetic control of Apigenin di-C-glycosides biosynthesis in bread wheat (Triticum aestivum L.) grain and their potential as yellow pigment of Asian alkaline noodles Student Name: Grace Yasmein Wijaya Pg # PhD
CHAPTER IV
Chapter IV: Apigenin di-C-glycosides (ACG) content and composition in grains of
bread wheat (Triticum aestivum) and related species
G.Y. Wijaya1,2 and D. Mares1
1School of Agriculture, Food and Wine, The University of Adelaide, PMB 1 Glen
Osmond, SA 5064, Australia
2Biotechnology Faculty, Atma Jaya Catholic University, Jl Jenderal Sudirman no 51,
Jakarta 12930, Indonesia
Journal of Cereal Science ; 2012: accepted paper
52
Journal of Cereal Science ; 2012: accepted paper
53
Chapter IV: Apigenin di-C-glycosides (ACG) content and
composition in grains of bread wheat (Triticum aestivum L.)
and related species
4.1 Introduction
Apigenin di-C-glycosides (ACGs) are present in the grain of bread wheat and other
related cereals primarily as one or two sets of Wesseley-Moser isomers containing
either arabinose and glucose (ACG1) or arabinose and galactose (ACG2) on the A ring
of apigenin. These compounds may contribute to the yellow colour of wheat-based
products made under alkaline conditions and in addition, have possible roles in a
number of plant physiological processes and human health. However, despite their
diverse and important roles, the biosynthesis of these compounds in plants is still not
well understood.
In wheat (Triticum aestivum L.) grain, Asenstorfer et al. (2006) reported significant
variation in the content of ACG1 and ACG2 and the ratio ACG/ACG2 for a small set of
Australian wheat cultivars. It is unclear whether the differences in ACG1 and ACG2
content, which is reflected in the ratio, are the result of two different C-
hexosyltransferases, C-glucosyltransferase and C-galactosyltransferase, or a single C-
hexosyltransferase that recognizes both uridine 5′-diphosphoglucose (UDP-glucose) and
uridine 5′-diphosphogalactose (UDP-galactose).
The aims of this investigation were to survey genetic variation for ACG content and
composition in hexaploid bread wheat (Triticum aestivum L.) and to examine ACGs in
54
the putative progenitors of hexaploid wheat, F1 grains derived by crossing bread wheat
parents with different ACG phenotype, Chinese Spring nullisomic-tetrasomic lines and
chromosome substitution stocks as a first step towards understanding the mechanisms
involved in their biosynthesis and genetic control.
4.2 Material and Methods
4.2.1 Plant materials
Seventy bread wheat (Triticum aestivum L.) genotypes sourced primarily from
Australian breeding programs, but including a small number of varieties of
miscellaneous origin, were grown as single twin row plots, 4 m long, at Turretfield,
South Australia in 2005. The harvested grains were analysed for ACG content and
composition in order to survey variation for these traits. Genotypes surveyed were as
follows (Supplemental material 4.1):
a) Cultivars released by Australian breeding programs – Batavia, Baxter, Cook,
Cunningham, EGA Gregory, EGA Hume, Hartog, Janz, Kennedy, Lang, Spica, Tasman
(Queensland); Gabo, Gamut, Gatcher, Sunco, Suneca, Sunfield, Sunlin, Sunvale,
Ventura (northern New South Wales); Avocet, Diamondbird (southern New South
Wales); Annuello, Chara, Meering, Silverstar (Victoria); Angus, Aroona, Frame,
Halberd, Krichauff, Kukri, Spear (South Australia; Canna, Carnamah, Cascades,
Cranbrook, GBA Ruby, Reeves, Westonia (Western Australia); b) Genotypes from the
University of Adelaide pre-breeding program - DM03.122/WI21121.1151,
DM03.122/WI21121.1442, DM03.24.b.241, DM03.24.b.248, DM03.24.b.281,
DM5686*B12, Sunco/Indis.82, SW95-50213/Cunningham.763, SW95-
50213/Cunningham.799, and c) Miscellaneous – AUS1408, Indis (Africa); Chinese
Spring, ChuanYu12, ChuanMai18, Jing Hong (China); Haruhikari (Japan); Ciano, Seri,
55
synthetic derived hexaploid wheats AUS29565, AUS29572, AUS29604, AUS30330
(Mexico); Condor high molecular weight glutenin biotypes 17 and 19, SUN325B,
Yellow Kite (University of Sydney); QT7475 (Leslie Research Centre, Queensland);
AUS1490 (Australian Winter Cereals Collection, Tamworth, New South Wales).
In 2009, 29 genotypes selected from this set to cover the range in ACG content were
sown in randomized replicated trials (twin row x 4 m plots) at 2 locations: Turretfield
Agricultural Research Centre (TARC), South Australia (34.97 oS latitude and 138.63 oE
longitude) and Waite Campus, University of Adelaide, Urrbrae, South Australia (34.55
oS latitude and 138.83 oE longitude). TARC is located on red-brown earth in the
livestock-cereal zone 55 km north of Adelaide at 115m elevation with mean annual
minimum and maximum temperatures of 12.2 oC and 22.3 oC respectively and 542.2
mm rainfall, of which 450.6 mm occurred during April-Dec 2009 (Australian Bureau of
Meteorology, Climate Information, online data access: March 2nd, 2011). The Waite
campus is located on the black cracking clay soil of the Adelaide plains at 116 m
elevation with mean annual minimum and maximum temperatures of 10 oC and 22.5 oC
respectively and 467.3 mm rainfall, of which 451.6 mm occurred during April-Dec
2009. The results from this field trial were required in order to gain a preliminary
estimate of the effects of genotype (G), environment (E) and GxE on ACG content and
composition.
In addition, accessions of Triticum monococcum, Triticum uratu, Aegilops tauschii,
Triticum durum, Triticum spelta, Aegilops speltoides, Triticum dicoccum, Triticum
polonicum, Triticum turgidum, Triticum diccoides, and Triticum carthlicum (section
3.2.1); the full set of 42 nullisomic-tetrasomic lines of Chinese Spring (section 3.2.1)
56
and the Chinese Spring/Triticum spelta chromosome substitution set (section 3.2.1)
were all subsequently grown in a glasshouse at the Waite Campus of The University of
Adelaide to produce the seed used for analysis.
Reciprocal F1 grain, Sunco/Tasman, Tasman/Sunco, Gamut/Reeves and Reeves/Gamut,
were produced by crossing 2 sets of parents. In each case the female was the first named
cultivar in the cross. For analysis, three replicates of F1 and parental grains from
glasshouse-grown plants, each consisted of 5 mature grains, were dissected into embryo
and de-embryonated portions (endosperm and seed coat) which were then compared
with whole grains.
4.2.2 Apigenin di-C-glycoside analysis
Methods for extraction and quantification of ACGs were as reported by Asenstorfer et
al. (2007) and Asenstorfer et al. (2006) with minor modifications, as explained in
Chapter III, section 3.4.1.1.
4.2.3 Experimental design and data analysis
Three replicate extractions were conducted on each grain sample. Two peaks,
previously identified as the isomers ACG1 and ACG2 (Asenstorfer et al. 2006), were
quantified as rutin equivalents (Chapter 3 section 3.4.2.1). The data was corrected for
losses during the SPE and drying steps based on the recovery of vanillin, the internal
standard (Chapter 3 section 3.4.2.1).
The proportion of the 2 groups of Wessely-Moser regioisomers was expressed as a
ratio, ACG1/ACG2. The amounts of ACG1, ACG2 and total ACG were expressed both
57
as concentration, g/g, and as g/grain. Concentration (g/g) because it is relevant to
the end-use of the grain and g/grain because it was anticipated that it would be less
affected by environmental factors. Environmental factors influence final grain weight
and can confound genetic effects for grain constituents that are synthesized early in
grain development.
The variation was analysed by one way ANOVA using GENSTAT version 14 (Chapter
3.4.3.2) with the variety and/or species included as treatment factors. Where significant
differences were detected, Tukey multiple comparisons at 95% confidence interval was
used to identify the different means.
For the field trial samples, the extractions were also conducted in 3 replicates.
Coefficient of correlation, probability associated with the Student‟s t-test, and ANOVA
were performed in GENSTAT software. The variety and location of the experiment
were included as treatment factors. The variance of each treatment factor and their
interactions were used in detecting genotype x environment (GxE) interaction. On the
second set of analysis of GxE interaction, the 2008 data of grain ACG trait analyses was
included as the third environment. The ANOVA of an unbalanced design was
performed using GENSTAT.
4.3 Results and discussion
4.3.1 Apigenin di-C-diglycoside analysis
Extracts of grain of bread wheat (T. aestivum) cultivars and accessions of related
species all contained the 2 major HPLC peaks representing the ACG diasterioisomers,
referred to as ACG1 and ACG2, previously identified by Asenstorfer et al. (2006)
58
(Supplementary material 4.2). The regioisomers of ACG1 and ACG2 were not resolved
by the HPLC system used in this investigation. A prior study (Asenstorfer et al. 2006)
concluded on the basis of NMR data that ACG1 and ACG2 consisted of racemic
mixtures of Wessely-Moser regioisomers. ACG1 had a retention time of 12.6 minutes
and was previously shown to consist of a mixture of apigenin-6C-arabinoside-8C-
glucoside (isoschaftoside) and apigenin-6C-glucoside-8C-arabinoside (schaftoside). The
second peak with retention time 13.3 minutes, ACG2, was a mixture of apigenin-6C-
arabinoside-8C-galactoside and apigenin-6C-galactoside-8C-arabinoside (Asenstorfer et
al. 2006). No other peaks observed had absorption spectra consistent with apigenin di-
C-glycosides. The ester bond in the ferulic acid and sinapic acid esters of ACG reported
by (Asenstorfer et al. 2006) is broken during extraction with hydroxylamine, liberating
the free phenolic acids and ACG. The ACG portion of the esters was therefore
measured together with the free form.
4.3.2 Apigenin di-C-glycoside concentration and content per grain
4.3.2.1 ACG concentration
The frequency distribution for total ACG concentration in the 70 Triticum aestivum L.
cultivars grown at Turretfield in 2005 approximated to a normal distribution with a
range 43 - 166 g (rutin equivalents)/g and a mean of 80 g/g (Figure 4.1A). The
concentrations of ACG1 and ACG2 in T. aestivum L. varied between 11 g/g and 70
g/g and between 29 g/g and 105 g/g respectively (Table 4.1). The ACG1, ACG2,
and total ACG contents were consistent with data previously reported by (Asenstorfer et
al. 2006).
59
The data for T. aestivum L. cultivars was subsequently compared with representatives of
wild and cultivated species related to bread wheat. Whilst the former were grown in the
field and the related species in a glasshouse, a small number of bread wheat cultivars
that were grown in both environments were shown to have similar ACG content
(supplemental material 4.3). As a consequence the comparison of the two sets of data
would appear to be useful in assessing the relative ACG phenotypes of bread wheat and
related species. Although only a limited number of accessions of each lower ploidy
species were examined, the results suggest that the concentrations of ACG in T. urartu
(AA), T. monococcum (AmAm ), and Ae. tauschii (DD) were significantly lower
(p<0.05) than T. aestivum (AABBDD), whereas Ae. speltoides (SS), T. dicoccum
(AABB), T. polonicum (AABB), T. turgidum (AABB), T.diccoides (AABB), T.
carthlicum (AABB), and T. durum (AABB) were within the range observed for T.
aestivum L. (Table 1). The low concentrations of ACG and in particular the glucose-
containing isomers, ACG1, in grains of T. urartu and T. monococcum would suggest
that the A genome would make only a minor contribution to ACG1 concentration in the
higher ploidy species. There could be only 1 key enzyme in A genome that is limiting
its contribution to ACG1 compared to B and D genomes. The other enzyme in the B
and D genomes could be very active and have a significant contribution in the presence
of both of these “very active enzyme” and the “limiting key enzyme” homeoforms in B
and D genomes. As a consequence it seems likely that the ACG1 in the tetraploid and
hexaploid species is contributed primarily by the B genome of Ae. speltoides and the D
genome of Ae. tauschii. The full data set is available as Supplementary data 1.
Triticum spelta, another hexaploid wheat species, had the highest concentration ACG1,
ACG2 and their total. There has been two tetraploid species proposed as candidates for
60
the progenitor of its A and B genomes, cultivated species Triticum diccoccum and wild
species Triticum diccoides. The wild species has higher ACG concentration than the
cultivated species. The D genome contributor of T. spelta, Ae. tauschii, has low ACG
concentration. In comparison with the Triticum diccocum/Aegilops tauschii AUS22445
lines, which content and concentrations of ACGs were between the two parents, T.
spelta has higher concentration of ACG1, ACG2 and their total.
4.3.2.2 ACG content per grain
There were significant differences (p<0.05) in 100 grain weight between and within
species (Table 4.2). The total ACG concentration was weakly but significantly
correlated with the 100 grain weight (r = 0.121, p<0.05). By comparison, there was a
stronger and highly significant correlation between ACG content per grain and 100
grain weight (r = 0.513, p<0.05). The diploid ancestral species have significantly
(p<0.05) lower 100 grain weight and ACG content per grain compared with the
tetraploids and hexaploids.
61
Figure 4.1. Frequency distribution for total apigenin di-C-glycoside (ACG) content
and composition in grain of 70 bread wheat, T. aestivum L, cultivars grown at
Turretfield, South Australia in 2005: A. Total ACG content in grain (g/grain), B. Total
ACG concentration (g/g), and C. Ratio ACG1/ACG2.
0
5
10
15
20
25
0.55 1.35 2.15 2.95 3.75 4.55 5.35 6.15 6.95 7.75 8.55
Frequency
Class interval of ACG content in the grain (g/grain)
0.55 1.35 2.15 2.95 3.75 4.55 5.35 6.15 6.95 7.75 8.55
0
5
10
15
20
25
30
20.00 37.00 54.00 71.00 88.00 105.00 122.00 139.00 156.00 173.00
Frequency
Class interval of ACG concentration in the sample (g/g)
20 37 54 71 88 105 122 139 156 173
0
5
10
15
20
25
30
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20
Frequency
Class interval of ACG1/ACG2 ratio
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2
62
Table 4.1 Range and means (+ SE) for apigenin di-C-glycoside (ACG) content in grain
of diploid, tetraploid, and hexaploid wheat species. The concentration and content are
presented as the concentration (g/g) and content in the grain (g/grain) of each type of
ACG (ACG1 and ACG2) and total ACG. The ACG1, ACG2, and total ACG data for all
lines are available as supplementary material 1.
63
The frequency distribution for total ACG content per grain in the 70 field grown T.
aestivum L. cultivars was bimodal with 83% less than 4.55 g/grain and 17% greater
than 4.55 g/grain (Figure 4.1B). By comparison, the diploid Aegilops species would
form a third group with ACG content less than 1.35 g/grain while the tetraploid
Triticum species would appear to be distributed within the range occupied by the bread
wheats (data for each genotype in Supplementary 4.1). Polyploidisation and/or
subsequent domestication and selection that have resulted in increased grain size (Table
4.1) appears to have been accompanied by increases in ACG concentration and in
particular, ACG content per grain, the latter trait being up to 10 fold greater than the
diploids.
Table 4.2 Means (+ SE) for 100 grain weight of the diploid, tetraploid, and hexaploid
wheat. a-i: indicate significant differences (p<0.01) in 100 grain weight based on
Duncan test of multiple comparison at 5% level.
T. monococcum 2.7 + 0.2 dT. urartu 2.3 + 0.1 eAe. speltoides 0.6 + 0.1 gAe. tauschii 1.4 + 0.1 fT. dicoccum 4.8 + 0.2 cT. durum 6.3 + 0.4 aT. polonicum 5.3 + 0.3 bT. aestivum 6.1 + 0.1 a
Species 100 grain weight (g)
64
4.3.2.3 ACG content of reciprocal F1 and parental grain
ACG1, ACG2 and total ACG in the de-embryonated fractions of grains (endosperm and
seed coat) of parental genotypes, Sunco, Tasman, Reeves and Gamut, represented
between 0 and 5.7 % of total grain ACG (Table 4.3). (Asenstorfer et al. 2006) reported
that endosperm tissue did not contain any apigenin di-C-glycosides so presumably the
ACG in the de-embryonated grains originated from the tissues of the grain coat
(pericarp + testa). Ingram (2006) and Rathjen et al. (2008) reported low levels of ACG
in the grain coat of developing wheat grains. By contrast with the parental genotypes,
the amounts in the de-embryonated fractions of F1 hybrid grains was significantly
higher and represented between 29.8-53.9 % of the total in the grain (Table 4.3). These
observations are difficult to explain. It was anticipated that the ACG phenotype would
be similar to the female parent in each case given that the grain coat represents maternal
tissue from the female parent used in the cross, besides the F1 hybrids were grown
together with their parents and their ACG analysis were performed at the same time.
These results were subsequently confirmed in a second series of crosses, Reeves/Gamut
and Gamut/Reeves, where the ACG content of the de-embryonated fraction of F1 grains
represented 41.8 and 48.2 % respectively of total grain ACG compared with only 0-5.7
% in the parents.
In the embryo fraction of F1 grains, the amount of ACGs tended to be similar to the low
ACG parent, except for ACG1 content of Tasman/Sunco. The similarity is consistent
with the presence of different alleles, with the lower activity allele being dominant. This
hypothesis would need to be confirmed by analysis of a segregating populations derived
from one or more of these F1s.
65
Table 4.3 Concentration, proportion and composition of the Apigenin di-C-glycosides
(ACGs) in de-embryonated grain and embryo of F1 reciprocal cross of Sunco-Tasman
and Gamut-Reeves parent pairs.
De-embryonated grainSunco 0.12 + 0.02 0.05 + 0.00 0.16 + 0.02 4.75 + 0.34 2.42 + 0.30Tasman 0.05 + 0.00 0.05 + 0.00 0.10 + 0.00 2.14 + 0.30 0.92 + 0.09Sunco/Tasman 2.53 + 0.08 0.68 + 0.08 3.21 + 0.12 53.88 + 3.12 3.84 + 0.41Tasman/Sunco 0.47 + 0.07 0.55 + 0.04 1.01 + 0.10 29.84 + 3.88 0.85 + 0.08Reeves 0.00 0.00Gamut 0.19 + 0.03 0.05 + 0.01 0.24 + 0.03 5.67 + 1.91 3.54 + 0.36Reeves/Gamut 0.41 + 0.00 0.90 + 0.11 1.32 + 0.11 41.82 + 3.89 0.47 + 0.06Gamut/Reeves 1.41 + 0.20 0.53 + 0.03 1.93 + 0.21 48.24 + 2.79 2.67 + 0.36
EmbryoSunco 1.85 + 0.18 1.42 + 0.16 3.27 + 0.34 95.25 + 0.34 1.3 + 0.03Tasman 1.71 + 0.15 2.86 + 0.29 4.57 + 0.44 97.86 + 0.30 0.6 + 0.01Sunco/Tasman 1.15 + 0.17 1.66 + 0.26 2.81 + 0.43 46.12 + 3.12 0.7 + 0.01Tasman/Sunco 1.04 + 0.10 1.37 + 0.10 2.41 + 0.20 70.16 + 3.88 0.8 + 0.02Reeves 0.67 + 0.06 1.26 + 0.13 1.92 + 0.19 100.00 + 0.00 0.5 + 0.00Gamut 2.34 + 0.47 2.30 + 0.49 4.63 + 0.96 94.33 + 1.91 1.0 + 0.02Reeves/Gamut 0.71 + 0.07 1.14 + 0.10 1.84 + 0.17 58.18 + 3.89 0.6 + 0.01Gamut/Reeves 0.79 + 0.10 1.30 + 0.22 2.10 + 0.31 51.76 + 2.79 0.6 + 0.03
Whole grain Sunco 1.97 + 0.20 1.46 + 0.17 3.43 + 0.36 1.35 + 0.02Tasman 1.75 + 0.15 2.91 + 0.29 4.66 + 0.44 0.60 + 0.01Sunco/Tasman 3.69 + 0.24 2.33 + 0.32 6.02 + 0.55 1.61 + 0.12Tasman/Sunco 1.50 + 0.04 1.92 + 0.07 3.43 + 0.10 0.78 + 0.02Reeves 0.67 + 0.06 1.26 + 0.13 1.92 + 0.19 0.53 + 0.00Gamut 2.53 + 0.45 2.35 + 0.48 4.88 + 0.93 1.09 + 0.03Reeves/Gamut 1.12 + 0.07 2.04 + 0.08 3.16 + 0.13 0.55 + 0.03Gamut/Reeves 2.20 + 0.26 1.83 + 0.24 4.03 + 0.47 1.21 + 0.09
~ ~ ~ ~
100.00
Lines ACG content (g/grain) % of total ACG in the grain
ACG composition (in ratio of
ACG1/ACG2)ACG1 ACG2 Total
66
4.3.2.4 ACG content of nullisomic-tetrasomic lines of Chinese Spring and
Chinese Spring/Triticum spelta chromosome substitution lines
Results for total ACG (g/grain) in nullisomic-tetrasomic lines of Chinese Spring were
either generally inconsistent or not significantly different from Chinese Spring. Only in
5 instances were both individuals of a nullisomic pair similar to one another and
significantly different from Chinese Spring. ACG content/grain in lines nullisomic for
chromosomes 1B, 2B, 5A, and 5D (means ACG of 3.5, 2.8, 3.4, and 2.9 μg/grain
respectively) were lower than Chinese Spring (mean ACG of 5.8 μg/grain)
(supplemental material 4.4). None of the Chinese Spring nullisomic-tetrasomic lines
contained zero ACG suggesting that variation in ACG content is associated with more
than one gene. By comparison, in the Chinese Spring/T.spelta chromosome substitution
series, only the line containing T.spelta 7B, with mean 9.1 μg/grain, had total ACG
content per grain significantly greater (p<0.05) than Chinese Spring control (6.7
μg/grain), but similar to T. spelta (7.6 μg/grain) (supplemental material 4.4). The
remaining Chinese Spring/T.spelta chromosome substitution lines were similar to
Chinese Spring. Further investigation using populations derived from parents with
contrasting total ACG phenotypes will be required to resolve the issue of number and
location of genes involved in determining variation in total ACG.
4.3.2.5 Relative effects of genotype and environment on ACG content
A significant correlation was obtained for total ACG concentration (g/g) of the 29 T.
aestivum lines harvested from Urrbrae and Turretfield field trials in 2009 (r = 0.544,
p<0.05). Similar data were analysed to estimate the proportion of observed variation
explained by genotype (G), environment (E) and GxE. The genotype x environment
interaction (GxE) was not significant while 34.7 % of the variation was due to
67
environment and 52.2 % was due to genotype. Significant correlations (p<0.05) were
also obtained when comparing total ACG content per grain (g/grain). For this trait,
genotype x environment accounted for 13.2 % of the variation, while 5.0 % variation
was due to environment and 74.2 % was due to genotype. The lower contribution from
genotype when data was expressed as a concentration (g/g) rather than per grain is
possibly a reflection of the effects of environment during the later stages of grain filling
impacting on final grain weight and greater or less dilution with starch. Comparison of
genotypes grown in a broader range of environments and years would be required to
define the relative contributions of genotype and environment to observe variation in
ACG phenotype more accurately.
Significant correlations were also obtained for concentration and content of ACG1 and
ACG2 (g/g and g/grain) of T. aestivum L. lines for grain harvested from Urrbrae and
Turretfield. Again, genotype was the major source of observed variation. Similar results
were also obtained when the ACG trait data from 2008 was included as one of the
environmental condition. There was no significant GxE for any of the ACG traits, and
genotype was the major source of variation.
4.3.3 Apigenin di-C-glycoside composition, ACG1/ACG2
The ratio of ACGs, ACG1/ACG2, indicates the relative proportions of C-glucosylation
and C-galactosylation, specifically, a low ratio indicates a higher proportion of
galactose containing ACGs. The ratio of ACG1/ACG2 in the grain of the T. aestivum L.
genotypes sampled from Turretfield in 2005 varied between 0.3 and 1.2 (Figure 4.1C).
The frequency distribution contained 2 distinct groups, a large group of cultivars (88.6
%) with low ACG1/ACG2 ratio (between 0.3-0.8) and a smaller group (11.4 %) with
68
high ACG1/ACG2 ratio (above 0.9). No cultivars were observed with ACG1/ACG2
ratio between 0.8-0.9. These results suggest the presence of different alleles at one locus
associated with synthesis of ACG1 and ACG2. The mean ACG1/ACG2 ratios for
Turretfield and Waite trials were strongly correlated (r = 0.83), indicative of a high
heritability for this trait.
ACG1/ACG2 for T. urartu and T. monococcum ranged from 0.075 to 0.28, lower than
for T. aestivum L. cultivars, whereas the ratio for Ae. tauschii was between 0.7 and 0.86.
Ae. speltoides and the wild and cultivated tetraploid species were within the range for
the main group of T. aestivum L. cultivars.
4.3.3.1 ACG composition and pedigree of Triticum aestivum L. cultivars
A high ACG1/ACG2 ratio for Sunco and Sunvale, backcross derivatives of the variety
Cook, reported by Asenstorfer et al. (2006) was confirmed in this study (Supplemental
material 4.1). However, other cultivars, Cunningham and Janz that also have Cook in
their pedigree (Supplemental material 4.5) had a low ratio (0.5 and 0.7 respectively).
The other parent of these low ratio cultivars can be traced back to Condor and 3-AG-3
(Martynov & Dobrotvorskaya 2006). Pedigree related cultivars with low ACG1/ACG2
ratio, Tasman, Suneca, Kennedy, and Hartog (Supplemental material 4.6) could be
traced back to a low ratio cultivar, Ciano. The other parent of Tasman can also be traced
back to Condor and 3-AG-3. There are 2 lines of Condor with different ratio
phenotypes, 1.1 and 0.7 (supplemental material 4.1), while 3-AG-3 can be traced back
to Chinese Spring (Sears, 1981 in Martynov & Dobrotvorskaya 2006), which is a low
ratio variety (0.7, Supplemental material 4.1). These observations support the
hypothesis that ACG1/ACG2 ratio is genetically controlled.
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4.3.3.2 ACG1/ACG2 ratio in reciprocal F1 grains and their parents
Analysis of whole grain, embryo and de-embryonated grain of parental lines and F1
(Table 4.3) suggested that regulation of the ratio, ACG1/ACG2, may be different in
embryo and non-embryo tissues of the grain. ACG1/ACG2 ratio for de-embryonated
grain of the parental genotypes was greater than for embryos except for Reeves, where
no ACGs were detected in the non embryo portion (Table 4.3). Embryos from the F1
grains of Sunco/Tasman, Tasman/Sunco, Gamut/Reeves, and Reeves/Gamut have a low
ACG1/ACG2 ratio similar (p<0.01) to the low ratio parents Tasman or Reeves (Table
4.3). This suggested that the ratio was genetically inherited, with the low ratio
phenotype, associated with a higher proportion of C-galactosylation, being dominant. In
the de-embryonated grain fractions of each reciprocal cross, the phenotype was more
similar to that of the female parent used in the cross. This is consistent with the ACGs
being located in the maternal grain coat tissue of the de-embryonated grain portion of F1
grains. The ACG1/ACG2 ratios of the F1 grain (whole grain, non-de-embryonated)
were similar to the female parents.
4.3.3.3 ACG composition of nullisomic-tetrasomic lines of Chinese Spring
Analysis of the 42 nullisomic-tetrasomic lines of Chinese spring indicated that the pairs
of stocks nullisomic for 1B, 7B, and 7D had ACG1/ACG2 ratios significantly different
from the parent Chinese Spring. Lines lacking chromosome 1B or 7D had very low
ACG1/ACG2 ratios similar to cultivars Ciano and Tasman, whereas for lines lacking
chromosome 7B the ratio was higher than Chinese Spring and similar to cultivars Sunco
and Cook (Figure 4.3). These results suggest that chromosomes 1B, 7B and 7D contain
QTL associated with variation in synthesis of ACG1 or ACG2. Despite the substantial
differences in ratio, the total amount of ACG per grain in lines lacking 7B or 7D were
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not significantly different to the Chinese Spring parent except for the Nulli 7D-tetra 7B
line (supplemental material 4.4). The similarity in phenotypes between the lines
nullisomic for chromosome 7B and the high ratio wheat cultivars such as Sunco further
suggests that these cultivars may have a null, non-functional or low activity allele at a
QTL on chromosome 7B.
Elimination of chromosome 7B in Chinese Spring 7B nullisomic lines resulted in an
increase in ACG1/ACG2, i.e. a relative increase in the glucose-containing isomer,
possibly indicating the presence of a C-glycosyltransferase on 7B with specificity for
UDP-galactose. A similar phenotype in the pedigree-related cultivars Cook, Sunco, and
other high ratio cultivars could be explained by a deletion or mutation of a gene
controlling this enzyme. The observation that high ACG1/ACG2 ratio was inherited as
a recessive trait is consistent with this proposal. A doubled haploid population derived
from a cross between Sunco and Tasman is examined in Chapter 6 to resolve this
question.
The tetrasomic 7B lines have a lower ACG concentration than Chinese Spring, while
the N7DT7A line has a similar ACG concentration. All other chromosome 7
nullisomic-tetrasomic lines have a higher concentration than Chinese Spring. This could
indicate that there is a represser of ACG synthesis on chromosome 7B, with the
tetrasomic lines of 7B having 2 copies, resulting in greater repression of ACG content.
Significant differences in ACG1/ACG2 ratio were also observed with lines lacking 4A
and 5B chromosomes, however, the differences between these two lines and Chinese
71
Spring lines were very small. Nevertheless, this may indicate the presence of minor
QTL for ratio on these chromosomes.
Figure 4.3 Content and composition of the 2 types of apigenin di-C-glycosides (ACG1
and ACG2) in the grain of the group 7 chromosome nullisomic-tetrasomic lines of
Chinese Spring compared with Cook, Ciano, Tasman, and Sunco. The comparisons of
the ACG1 and ACG2 content describe the differences in ACG1 to ACG2 composition
in the grain. White bars represent ACG1, red bars represent ACG2. Bars represent SE
of means.
4.3.3.4 Correlation among ACG components
The amounts of ACG1 and ACG2, showed a highly significant positive relationship (r =
0.886 and 0.952, p<0.05) with total ACG content. There was also a significant positive
correlation between amounts of ACG1 and ACG2 although this correlation was
0.0
20.0
40.0
60.0
80.0
100.0
120.0
Ciano Chinese Spring
(wild type)
N7AT7B N7AT7D Cook Sunco N7BT7A N7BT7D Tasman N7DT7A N7DT7B
ACG concentration (g/g)
Lines
72
possibly confounded by the large proportion of genotypes with low ACG1/ACG2 ratio.
ACG1 but not ACG2 or total ACG was significantly correlated with ACG1/ACG2
ratio. Control of the ratio therefore appeared to be independent of control of total ACG
but depended on ACG1 concentration.
4.4 Conclusions
Significant genetic variation was identified for both total ACG content and
ACG1/ACG2 ratio. Consequently, it should be possible to select wheat varieties with
higher ACG content. Several observations indicate that genetic mechanisms that control
total ACG content act prior to the glycosylation step in biosynthesis; namely the strong
correlation between amounts of ACG1, ACG2 and total ACG, and the lack of
significant correlation between ACG content and ACG1/ACG2. In addition,
preliminary investigations of genotypes differing in total ACG content suggested that a
lower content may be partly explained by a lower activity of enzymes such as chalcone
isomerase, an enzyme catalyzing an early step in flavonoid biosynthesis (Kashem &
Mares 2002). Variation in ACG content could reflect the relative activity of the
enzymes located early in the flavonoid pathway, competition with other branches of the
pathway for flavone precursors and/or UDP sugars, or possibly regulation of flavonol-2-
hydroxylase, the first committed step in the proposed branch in the flavonoid
biosynthesis pathway leading to ACG.
The ACG ratio, whilst possibly not of interest commercially, provides an avenue
towards understanding the mechanisms and regulation of C-glycosylation. No ACGs
containing the same sugar residue at both C6 and C8 were identified and all ACG
isomers contained arabinose attached to either C6 or C8. Since changing the ratio did
73
not affect total ACG content, it seems possible that the proportions of ACG1 and ACG2
depended on either the relative sizes of the available pools of UDP-glucose and UDP-
galactose, the activity of the epimerase that catalyses their interconversion or variation
in the activity and specificity of the C-glycosyltransferases. Different alleles of genes
coding for C-hexosyltransferase may result in differences in UDP-sugar recognition.
Elimination of chromosome 7B in Chinese Spring 7B nullisomic lines resulted in an
increase in ACG1/ACG2, i.e. a relative increase in the glucose-containing isomer,
possibly indicating the presence of a C-glycosyltransferase on 7B with specificity for
UDP-galactose. A similar phenotype in the pedigree-related cultivars Cook, Sunco, and
Sunvale and other high ratio cultivars could be explained by a deletion or mutation of a
gene controlling this enzyme.
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77
Chapter V: Contribution of Apigenin di-C-glycoside (ACG) to
the colour of yellow alkaline noodles (YAN) in comparison to
that of Lutein
5.1 Introduction
Yellow alkaline noodles (YAN) are an important end-product for Australian wheat
throughout South East Asia and Japan (QDPI 2009). The yellow colour is contributed
by xanthophylls, primarily lutein and its fatty acid esters, apigenin di-C-glycosides
(ACG1 and ACG2, Figure 2.2) and yellow colour additives used by the manufacturer
(Asenstorfer & Mares 2006, Asenstorfer et al. 2006, Fortmann & Joyner 1978, Morris
et al. 2000, Wang 2001, Ward et al. 1995). Xanthophylls are present at relatively low
concentration in bread wheat and give colour ranging from white to pale yellow to
noodle dough (Parker et al. 1998). By contrast, ACGs remain colourless in water or acid
solution and give the yellow colour only after alkaline solution is added during the
preparation of YAN (Asenstorfer et al. 2006). Raising the levels of the endogenous
compounds that contribute to the yellow colour could reduce, and potentially eliminate
the need for colour additives and add value to Australian wheat. In particular, raising
the ACG content could improve the YAN colour derived from natural endogenous
compounds without impacting on the colour of flour or a range of other wheat-based
foods such as bread that are traditionally creamy to white in colour.
The contribution of xanthophylls to noodle colour is well established but there is only
limited information for ACGs. Typically, for YAN prepared with alkaline salts but no
colour additives, the increase in CIE (Commission Internationale l‟Eclairage) b*
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compared with control white salted noodles (WSN) is around 6 units (Wijaya et al
2009). However, how much of the yellow colour developed in the presence of alkaline
salts is due to ACGs has not been quantified. By comparison, the b* of commercial
samples of YAN sourced from the supermarket can be as high as 45 – 55 (Wijaya et al.
2010) of which 20 – 30 b* units would appear to be due to the presence of additives
such as tartrazine and sunset yellow. In this context it is not clear whether there is
sufficient genetic variation for ACG content to firstly, allow breeding wheat varieties
for better YAN colour and secondly, to estimate how much ACG would be required to
significantly reduce or eliminate the need for colour additives.
Previous studies have relied on a spectrophotometric assay for ACG but these results
have recently been shown to be confounded by interaction between the extractant and
flour constituents and therefore not specific for ACGs (Asenstorfer & Mares 2006). In
addition, the ACGs appear to be located in the embryo and seed coat (Fortmann &
Joyner 1978, Ingram 2006, Miskelly 1996, Rathjen 2006), which would limit their
recovery in flour during the milling process.
The aims of this study were to:
compare the lutein and ACG content of grain and flour in a range of bread wheat
genotypes
determine the relationships between these traits and both total YAN yellow
colour and the component of yellow colour developed specifically in the
presence of alkaline salts
estimate the impact of the available genetic variation for ACG content on
improving the yellow colour of YAN, and
79
compare the recoveries of ACG and lutein in flour.
To achieve these aims, the lutein and ACG content of grain and flour were compared,
and their correlation with both the total yellowness of YAN and the yellow colour
developed specifically in the presence of alkaline salts examined. In addition, the
contribution of ACG to the yellow colour of YAN was predicted using a standard curve
of YAN b* versus added rutin and compared the observed change in b* due to the
presence of alkali. In turn, the potential increase in colour if all the grain ACG could be
recovered in flour was calculated. The effects of milling were determined by comparing
grain and flour lutein and ACG content and compared in relation to the grain tissue
locations of these substances.
5.2 Materials and Methods
5.2.1 Plant materials
Grain of twenty eight Australian commercial bread wheat (Triticum aestivum L.)
cultivars representing all the wheat production zones in Australia was produced in a
field trial at Turretfield, South Australia in 2005 and stored at low humidity and room
temperature in sealed containers. Cultivars and their region of origin are: Ventura,
Sunvale, Sunco and Sunlin (Northern New South Wales); Diamondbird (Southern New
South Wales), Cunningham, EGA Gregory, Hartog, Janz, EGA Hume, Kennedy, Lang,
Batavia and Baxter (Queensland); Spear, Frame, Halberd, Krichauff and Kukri (South
Australia); Chara, Meering, Silverstar and Annuello (Victoria); GBA Ruby, Cascades,
Carnamah, Reeves, and Westonia (Western Australia). To provide sufficient sample
size for Bühler Milling, nine of these cultivars from 2005 (Sunvale, Sunco, Hartog,
80
EGA Hume, Halberd, Krichauff, Silverstar, GBA Ruby and Reeves), were grown as
larger plots in Turretfield, in 2009.
Grain of a large bulk of cultivar Suneca were used as standard throughout the flour
milling experiments, while a bulk flour sample of cultivar Sunvale was used to quantify
the effect of addition of different amounts of rutin on YAN colour.
5.2.2 Preparation of flour and noodles
5.2.2.1 Grain milling
Three experimental mills were used: Udy cyclone mill, Quadrumat Junior mill
(Brabender, Germany), and Bühler mill (Bühler Ag, Switzerland) depending on the
sample size and/or the need for milled flour. The Udy cyclone mill was used to prepare
whole meal flour for analysis of total grain content of ACG or lutein. The Quadrumat
Junior mill requires at least 50g of grain samples, and is suited to the rapid and simple
preparation of flour substantially free from bran and pollard in a single step. The Bühler
mill is a more sophisticated method than the Quadrumat mill, capable of milling up to 5
kg grain, and separating the bran and pollard fractions from the flour in a progressive
particle size reduction and sieving process.
In this experiment, the Udy cyclone mill fitted with a 0.1 mm screen to control particle
size was used to grind the grain samples to a fine whole meal (Asenstorfer et al. 2006).
A Quadrumat Junior mill was used for small samples from the 2005 trial whereas the
Bühler mill was used to prepare higher quality flour from the 2009 samples. The flour
yields from the Quadrumat Junior and Bühler were in the range of 65%-72% and 60%-
71% respectively. For the Quadrumat Junior, 150g was weighed and pre-conditioned
81
overnight to 15% moisture prior milling. Samples of Suneca were milled every 7
samples to monitor the performance of the mill. In the Bühler experiment, 5kg of grain
was preconditioned to 15% overnight prior to milling and pooled break, pooled
reduction, Bran and pollard fractions collected. Subsequently, the pollard fraction was
re-sieved to remove residual flour and retain a sieved pollard fraction.
5.2.2.2 Preparation of noodle sheets
YAN noodle sheets were prepared as described by Asenstorfer et al. (2006). Ten grams
of flour was mixed with 3.5 mL of sodium carbonate solution (2% w/v), in a small
stainless steel bowl using a paddle attached to an electric drill press. The mixture was
formed into a sheet by passing through a hand operated spaghetti machine several times.
To estimate the proportion of the yellow colour of YAN, which develops in the
presence of the alkaline conditions, white salted noodles (WSN) were used as a control.
WSN were prepared in the same way as YAN except that sodim carbonate was replaced
with sodium chloride. The YAN and WSN sheets and noodles obtained are shown in
Figure 5.1.
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Figure 5.1 Noodles and noodle sheets for measurements of b* and b*. A. YAN B.
WSN C. YAN sheet. B. WSN sheet.
5.2.3 Measurement of colour of YAN and WSN
The colour of YAN and WSN, was measured by CIE (Commission Internationale
l‟Eclairage) L*, a*, b* (Humphries et al. 2004, Oliver et al. 1992, Wyszecki & Stiles
1982) using a Dataflash 100 reflectance spectrophotometer (Datacolour International,
USA) at 0, 2, 4, and 24 hours. Initially, this instrument was calibrated with a white tile
and a black card.
L* measures changes in brightness on a 0 to 100 scale where 0 = black and 100 = white,
whilst a* measures variation in red-green colour range. The values of a* are close to
zero for wheat flour and therefore can effectively be ignored. The values of CIE b*
measure the yellow colour, which range from -60 (pure blue) to +60 (pure yellow). The
colour measurements for each noodle sheet were determined as the mean of duplicate
83
measurements. The amount of yellow colour developed specifically in response to the
alkaline pH was estimated as b* (YAN b*- WSN b*).
5.2.4 Analyses of yellow pigment content in grain and flour
5.2.4.1 ACG analysis of grain and flour
Extraction and quantification of ACGs of grains were performed according to
Asenstorfer et al. (2007) and Asenstorfer et al. (2006) with minor modifications
described in Chapter III section 3.4.1.1. A larger sample size, 0.5g, was extracted with 5
mL of 0.1 M hydroxylamine (Sigma, St Louis, USA) pH 7.0, spiked with 15L of
vanillin standard (Sigma, St Louis, USA), mixed for 24 hours prior centrifugation at
2100g for 10 minutes, then half the supernatant loaded onto a reverse phase SPE
column (StrataTM -X33m C18 polymorphic sorbent, Phenomenex, Torrance, CA,
USA) that had been preconditioned with methanol and H2O. The fraction containing
ACGs eluted from the column was spiked with 50L rutin, vacuum concentrated and
the residue resuspended in 1mL methanol (50%) for HPLC analysis. The rest of the
method was as described in section 3.4.1.1.
ACG content and composition traits were calculated as described in section Chapter 3,
section 3.4.2.1. The recovery of ACG in Quadrumat Junior flour was calculated as a
percentage of total grain ACG. For Bühler Mill, the proportion of ACG in the flour
were calculated as the total ACG in reduction and break flour fractions as a percentage
of the total ACG in all mill fractions, flour, bran and pollard. The ACG content in each
fraction was calculated as the concentration of total ACG multiplied by the amount of
the fraction recovered from milling.
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5.2.4.2 Lutein analysis of grain and flour
5.2.4.2.1 Lutein extraction and analyses
Lutein was extracted using a sequential method (Soriano et al. 2007) that was optimized
by Raoufi-Rad (2007). The whole meal samples (2 g) were extracted sequentially,
firstly with 10mL of methanol/tetrahydrofuran (1:1 v/v) containing 0.1% butylated
hydroxytoluene (BHT) and secondly with hexane, each for 2 hours, under nitrogen at
280C in a temperature regulated shaker. During the first extraction, -apo-8‟-carotenal
(50 L) was added as internal standard. After each extraction, centrifugation was
performed for 10 minutes at 3500 rpm following shaking, and the supernatant then was
transferred to a glass tube. The supernatants were pooled and then vacuumed dried and
purged with a stream of high purity nitrogen prior to storing for HPLC analysis. The
dried residues obtained were reconstituted with 1 mL methanol/tert-butyl methyl ether
(MTBE, 1:1 v/v), vortexed for 30 second. Quantification was performed by reverse-
phase HPLC analysis using C30 reversed-phase column protected by a C18 guard
column (Breithaupt et al. 2002). The mobile phase consisted of two solvents, A (81:15:4
methanol/MTBE/water) and B (90:10 MTBE/methanol). They were used at a flow rate
of 1 mL/min with following protocol: 100% A for 10 minutes, 0-50% B for 40 minutes,
50-100% B for 10 minutes, 0-100% A for 5 minutes and an isocratic elution with 100%
A for 5 minutes to condition the column (Breithaupt et al. 2002) modified according to
Raoufi-Rad (2007). Absorbance at wavelengths 445 was used in detection and
quantification of lutein. The lutein peak was detected at around 7 minutes, while peaks
of the monoester and diester forms of lutein were detected at around 32-34 minutes and
44-46 minutes respectively, which were verified by their spectrums.
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5.2.4.2.2 The use of internal and external standard solutions in lutein analyses
The use of -apo-8’-carotenal as internal standard
The -apo-8‟-carotenal was used as internal standard to enable correction of data for
losses during the extraction. Initially, the standard -apo-8‟-carotenal stock solution was
made up from 5mg powder in 1 mL methanol/MTBE (1:1 v/v)). This solution was
filtered by using filter paper (Whatman no 541, diameter 55mm). A serial dilution of
this standard were mas and the absorbances of these dilutions were measured by using
spectrofotometer (at 451nm wavelength). The dilution with 0.5 absorbance was used as
internal standard. The concentration of this -apo-8‟-carotenal standard was calculated
by using Lamber-Beer Law:
where:
A = absorbance (= 451nm).
coefficient of extinction of -apo-8‟-carotenal (1% g/mL = 139,500 at 451nm).
l = the path of the wavelength (= 1cm cuvet length).
Two replicates of controls contained blank samples (without whole meal or flour
materials) were spiked with 50 L of -apo-8‟-carotenal standard stock solution. The
analytical 450nm UV wavelength detected the peak of -apo-8‟-carotenal standard at
about 18 to 20 minutes, which was verified by its spectrum. The areas of the -apo-8‟-
carotenal peaks obtained from these controls and from the samples were then compared
and calculated to get the -apo-8‟-carotenal corrected area values as follows:
A = [C] x x l
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The use of xanthophylls to construct the standard curves
Th lutein standard curves were made by a serial dilutions of 1mg/mL xanthophylls in
MTBE, from 1 to 100 times. The areas of these xanthophyll standard dilutions were
then measured by HPLC at 445nm wavelength. The xanthophyll concentrations were
plotted as y axis, while the areas as x axis in Microsoft Excell worksheet (version
2007). A trendline and the coefficient of this standard curve were regenerated to
calculate the lutein content in the flour and whole meal samples.
The lutein content in the 2g samples with 1mL final dilution in MTBE (1:1 v/v) was
calculated follows:
In the absence of authentic lutein ester standards, the amounts of mono- and di-esters
were expressed as μg lutein equivalents. For the purposes of this investigation, total
lutein (lutein + lutein mono- and di-esters) was calculated.
5.2.5 Estimation of ACG contribution to yellowness of YAN
Since pure apigenin di-C-glycosides were not available commercially, a standard curve
was constructed using a closely related compound, rutin (an apigenin-C-glycoside).
area of -apo-8‟-carotenal pure std X Area of lutein area of -apo-8‟-carotenal std in each samples
-apo-8‟-carotenal corrected area X 1000 . standard curves coefficient sample weight (g)
87
Noodle sheets were prepared from Sunvale flour with the addition of rutin at 8.3, 16.6,
31.3, 62.5, 125, 250, 500, and 1000g/g according to the method described in section
5.2.2.2. Control noodle sheets were made from the same flour without any rutin
addition. The b* of the noodle sheets were measured at 0, 2, 4, and 24 hours as
mentioned in the section 5.2.3. The b* was calculated as b* of the noodles with added
rutin – b* of control noodles.
To estimate the ACG constribution to b*, standard curve was constructed by plotting
the rutin concentration that added to the noodle sheets againstb*. This was performed
for each time measurements (0, 2, 4 and 24 hours) to follow the effect of each rutin
addition into noodle dough to the change in the yellowness of the noodles.
5.2.6 Data analysis
The variation in the ACG and lutein content were analysed by one way ANOVA with
GENSTAT 14 (Chapter 3 section 3.4.2.2) with the variety included as treatment factor.
When significant differences were detected, LSD at p=0.05 was used to identify the
different means.
The flour recovery from Quadrumat Junior milling was calculated as percentage of the
weight of the starting material. Meanwhile, the flour recovered from Bühler milling was
calculated as percentage of break flour and reduction flour per total grain weight.
Correlations between ACG content or, (%) recovery in flour, and YAN (b*) or YAN
b* were determined by simple regression analysis using GENSTAT software (version
14; VSN International, Hemel Hempstead, UK). The b* or b* was the response variate
while the ACG content or (%) recovery in flour was the explanatory variate.
88
GraphPad Prism (version 5.04; GraphPad Software, Inc., CA, USA) was used to plot
the curve relating change in YAN b* (b*) to amount of added rutin to wheat flour.
b* data at 0, 2, 4, and 24 hours was plotted as non-linear regression curves. The one
site-specific binding of Binding-Saturation equation was used to generate the
relationship between rutin concentration and YANb*:
Y = a*X/(b + X)
Y is the b* of YAN, X is the concentration of rutin (μg/g) while a and b are constants.
5.3 Results and Discussion
5.3.1 ACG and lutein content in wheat grain and flour
The mean ACG concentration in grain was 71.6g/g (Table 5.1) while the concentration
in flour was 19.3g/g. By comparison, the mean lutein concentrations in wheat grain
and flour were similar to each other, 1.086g/g and 1.011g/g respectively, and much
lower than ACG concentrations.
The average recovery of lutein in Quadrumat Junior mill flour was 90% (Table 5.1) and
there was a very strong correlation (r = 0.941) between the lutein concentrations in
grain and flour. By contrast, only 30%, on average, of grain ACG was recovered and
there was no correlation between grain and flour ACG concentration (r = -0.007). Thus,
not only was the recovery of grain ACG in flour very low, but the amount recovered in
flour was seemingly not determined by the grain ACG concentration but rather by the
milling performance of the wheat.
89
5.3.1.1 The effect of milling on the proportion of ACG and lutein in
relation to their tissue location in the grains
The composition of the flour recovered during milling reflects firstly, how cleanly the
starchy endosperm is separated from the other tissues comprising the grain, and
secondly, the tissue location of grain constituents. Earlier work reported by Asenstorfer
& Mares (2006) indicated that ACGs were concentrated in the embryo or germ tissue
with lower concentrations in the grain coat but seemingly none in the starchy
endosperm. These observations were later confirmed by Ingram (2006). It was
concluded therefore that the ACG content in flour was dependent on the level of
contamination of flour by germ and/or bran. Flour ACG1 as a proportion of the total
flour ACG was higher than in grain with means of 44.6% for flour and 32.4%
respectively, while the proportion of ACG2 in the grain is higher than in the flour with
means 67.6% and 55.4% respectively (Table 5.2 and supplemental materials 5.2 for the
details). These differences were reflected in the ACG1/ACG2 ratios, which were higher
in flour than in the grain, 0.6-1.3 in flour (mean = 0.8) and 0.3-1.0 (mean = 0.5) in the
grain. The results indicate that more ACG2 than ACG1 is removed with the bran and
pollard during milling and imply that the proportions of ACG1 and ACG2 in grain coat
and embryo tissues are different. Furthermore, these observations could provide a clue
to which grain tissue, embryo or grain coat, is the main source of the ACG in flour.
Currently there is insufficient data available to allow resolution of this question.
The xanthophylls present in the grain were predominantly in the form of free lutein
(26.4-40.6%, mean = 34) and its mono- (25.3-44%, mean = 34) and di-fatty acid esters
(15.4-41.5%, mean =32) (supplemental material 5.3). By comparison, the proportions of
90
the different lutein species in Quadrumat Junior mill flour were: free lutein (17.9-
32.2%, mean = 25), mono-esters (27.2 – 37.8, mean = 34) and di-esters (31.8 – 53.8,
mean = 41). Thus the proportion of total lutein present as free lutein in the flour was
significantly lower (p<0.01) than the proportion in grain and conversely the proportion
present as di-esters was significantly (p<0.001) higher than grain. There appeared to be
no significant difference (p<0.05) in monoesters.
Previous studies reported that there were little or no esters in grain at maturity but that
esters form during grain storage depending on temperature and humidity (Kaneko et al.
1995, Kaneko & Oyanagi 1995). The high proportion of ester forms in the grain and
flour in this study is presumably a reflection of the grains having been stored at low
humidity since 2005 prior the experiment in 2009.
Lutein was distributed almost evenly in the grain tissues according to Hentschel et al.
(2002), however, by contrast, Law (2005) reported higher concentrations of lutein in the
embryo (up to 6 time the concentration in endosperm) than in other tissues. However, as
the embryo only represents 3% of the grain weight and most is removed by milling,
much of the lutein recovered in the flour originates from endosperm tissue (Soriano et
al. 2007). Law (2005) further reported that esters were present primarily in the
endosperm and seed coat whilst there appeared to be only very low amounts in the
embryo. These observations might explain the differences in the proportions of free
lutein and ester forms in flour compared with the grain. During milling it is anticipated
that most of the embryo tissue with its higher free lutein concentration would be
discarded in the germ fraction.
91
Table 5.1 Total ACG and lutein concentrations in grain and flour and the percentage
recovery in Quadrumat Junior mill flour.
Ventura 71 + 2.5 0.86 + 0.03 16 + 0.1 0.79 + 0.02 22 + 0.7 92 + 0.6Sunvale 81 + 0.2 0.76 + 0.08 14 + 1.0 0.66 + 0.00 18 + 1.2 89 + 3.1Sunco 95 + 4.8 0.74 + 0.02 16 + 1.4 0.58 + 0.03 17 + 1.3 79 + 1.6Diamondbird 51 + 2.8 0.95 + 0.01 11 + 1.6 0.80 + 0.03 22 + 2.4 85 + 1.7Sunlin 78 + 6.6 0.99 + 0.04 17 + 0.6 0.95 + 0.02 23 + 1.2 96 + 0.5Cunningham 92 + 3.2 1.00 + 0.06 18 + 0.8 0.87 + 0.03 19 + 0.2 87 + 2.2EGA Gregory 53 + 3.4 1.02 + 0.04 13 + 0.6 0.93 + 0.02 25 + 2.3 91 + 0.8Hartog 92 + 14.9 1.05 + 0.05 17 + 0.3 0.76 + 0.01 20 + 2.8 72 + 1.4Janz 72 + 4.9 0.88 + 0.02 20 + 2.0 0.86 + 0.03 28 + 2.7 97 + 1.9EGA Hume 68 + 1.6 0.83 + 0.03 19 + 1.2 0.75 + 0.01 28 + 1.4 91 + 0.5Kennedy 60 + 7.8 0.82 + 0.03 17 + 0.8 0.71 + 0.00 29 + 4.6 86 + 1.0Lang 105 + 9.6 0.72 + 0.04 19 + 1.4 0.70 + 0.02 19 + 3.2 98 + 2.0Batavia 55 + 3.8 1.18 + 0.03 15 + 1.7 1.18 + 0.00 28 + 4.5 100 + 0.8Baxter 63 + 2.8 0.76 + 0.04 16 + 0.9 0.66 + 0.02 26 + 1.5 88 + 1.5Spear 76 + 4.2 1.05 + 0.03 17 + 1.2 1.03 + 0.01 22 + 2.4 98 + 0.7Frame 93 + 8.6 1.01 + 0.05 19 + 0.7 1.16 + 0.00 20 + 1.3 90 + 0.7Halberd 109 + 4.6 1.10 + 0.05 25 + 2.3 1.06 + 0.05 22 + 1.4 88 + 0.9Krichauff 65 + 1.4 1.97 + 0.03 21 + 0.2 2.00 + 0.03 32 + 0.4 98 + 0.4Kukri 83 + 5.1 1.16 + 0.06 21 + 1.1 1.06 + 0.00 25 + 0.7 92 + 1.9Chara 54 + 3.5 1.01 + 0.17 18 + 0.6 1.21 + 0.09 34 + 2.8 96 + 0.5Meering 78 + 2.5 1.04 + 0.03 28 + 0.6 1.23 + 0.05 37 + 1.7 99 + 1.2Silverstar 43 + 1.8 0.95 + 0.02 25 + 1.1 0.82 + 0.03 59 + 2.7 86 + 1.9Annuello 56 + 4.4 1.37 + 0.05 21 + 2.7 1.13 + 0.06 39 + 5.8 84 + 3.6GBA Ruby 81 + 6.9 0.95 + 0.05 22 + 1.2 0.57 + 0.03 28 + 2.4 61 + 2.6Cascades 62 + 6.4 1.95 + 0.04 21 + 1.1 1.84 + 0.01 35 + 5.3 95 + 0.5Carnamah 63 + 8.1 1.43 + 0.07 27 + 1.2 1.26 + 0.01 45 + 7.0 89 + 0.5Reeves 43 + 0.9 1.03 + 0.09 27 + 2.1 0.94 + 0.05 61 + 6.2 92 + 1.1Westonia 62 + 3.4 1.86 + 0.02 20 + 1.4 1.80 + 0.00 32 + 3.3 97 + 2.1MaxMinMeans 72+ 3.3 1.09 + 0.10 19 + 0.8 1.01 + 0.10 29 + 2.0 89.8 + 1.6
43 0.72 11 0.57 17 61.0109 1.97 28 2.00 61 100.0
Cultivars Total content in grain (g/g) Total content in flour (g/g) % Recovery ACG Lutein ACG Lutein ACG Lutein
92
Table 5.2 Proportion of total yellow pigments in flour compared with grain; range and
means for 28 bread wheat cultivars. The ACGs are presented as ACG1 and ACG2 while
the luteins are presented as lutein, lutein-monoester, lutein-diester and total lutein-ester.
5.3.1.2 Comparison of Bühler and Quadrumat Junior Mills
As mentioned in the Materials and Methods section, the Bühler mill is a more
sophisticated experimental flour mill than the Quadrumat Junior mill and therefore
likely to provide a better indication of the way a wheat variety will perform in a
commercial flour mill. It was therefore of interest to determine whether the Bühler gave
a greater recovery of ACG and whether there was a stronger relationship between grain
and flour ACG concentration.
Total ACG concentration in Bühler flour ranged from 6.9-33.5g/g, with a mean of
18.3g/g (Figure 5.3 and supplementary material 5). This was not significantly
(p<0.001) different from that obtained with Quadrumat Junior Mill and perhaps more
significantly, one mill was not consistently better or worse than the other. Except for
EGA Hume, Krichauff and Silverstar, where the total ACG content recovered from
Bühler Mill were lower than from Quadrumat Junior (p<0.001).
ACG1 32.4 + 3.4 44.6 + 3.8ACG2 67.6 + 3.4 55.4 + 3.8
ACG1/ACG2 Ratio 0.5 + 0.1 0.8 + 0.1Lutein 34.1 + 0.6 25.2 + 0.7Monoester Lutein 34.0 + 0.8 33.8 + 0.5Diester Lutein 31.9 + 1.2 41.0 + 1.0Total Lutein-ester 65.9 + 0.6 74.8 + 0.7
31.867.8
26.425.315.459.4
17.927.2
40.644.041.573.6
32.237.853.882.1
Max Min MeansProportion in grain (%) Proportion in flour (%)
Max Min Means57.063.8
1.3
24.850.3
0.3
36.243.0
0.6
Pigment
49.775.2
1.0
93
Overall, recoveries were lower for the Bühler mill than Quadrumat Junior mill,–
presumably a reflection of the progressive particle size reduction and sieving which
gave flour that contained less contamination from the bran and germ tissues that contain
the ACGs. Concentration, the critical trait in terms of development of yellow colour in
YAN, appeared to show significant differences between varieties despite there being no
strong correlation between grain concentration and flour concentration. In terms of
variety improvement, selection for grain concentration, a relatively quick method,
would not be very useful. Rather selection would have to be on the basis of Bühler flour
concentration, a more involved procedure in view of the requirement for a milling step.
Before any firm conclusions could be reached, a more detailed study would be required
to assess the relative effects of genotype and environment on flour ACG concentration.
There were only relatively minor differences in flour recovery for the Bühler compared
with quite large differences for Quadrumat milling, an observation which would need to
be confirmed. However these preliminary results suggest that for this trait, Quadrumat
milling would not be very useful. Bühler flour ACG concentrations are higher than
Quadrumat flour concentrations for Sunco, Sunvale and Ruby. Interestingly, Sunco and
Sunvale are Australian Prime Hard wheat cultivars selected for high milling quality and
flour yield. Targets for breeding would be high recovery in Bühler flour and high flour
concentration.
94
Figure 5.2 ACG concentration (g/g) in Bühler mill (white bar) and Quadrumat junior
mill (red bar) flour of 9 cultivars of bread wheat. The error bars represent the standard
errors.
Figure 5.3 Recovery (%) of grain ACG in Bühler mill (white bars) and Quadrumat
junior mill (red bars) flours for 9 cultivars of bread wheat. The error bars represent the
standard errors.
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Krichauff Silverstar Halberd Sunco Ruby Hartog Reeves Sunvale Hume
Total ACG concentration in
flour (g/g)
Cultivars
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Krichauff Silverstar Halberd Sunco Ruby Hartog Reeves Sunvale Hume
Recovery of ACG (%)
Cultivars
95
5.3.1.3 The influence of grain physical properties on milling
The differences in milling recoveries of ACG between varieties may be a reflection of
the influence of the grain physical properties on milling. In particular, the softness or
hardness of the grain has been shown to influence the milling process (Greffeuille et al.
2005). Grain softness and moisture pre-conditioning influence the efficiency of
separation between bran and endosperm in flour milling (Edwards et al. 2007). In
maintaining partial dryness for ease of the bran removal, hard grain wheat requires
higher moisture than the soft grain to soften the endosperm and toughen the bran (Glenn
et al. 1991). In commercial milling practice, soft grain varieties are pre-conditioned to a
lower moisture content than hard grain varieties (Edwards et al. 2007). However, in this
experiment, all the varieties were hard-grained with the exception of Reeves and the
same moisture pre-conditioning was applied to all samples. This might explain the
differences in ACG recovery in the flour between the hard grain varieties (Sunco and
Sunvale) and the soft grain variety (Reeves), especially when the grains were milled
with the less sophisticated Quadrumat Junior mill.
Liyana-Pathirana and Shahidi (2006) reported the higher recovery of phenolic
compounds in soft compared with hard grain. Greffeuille et al. (2005) reported that the
breaking of wheat grain by milling occurred close to the aleurone layer, at the
interphase between tissues, and this determined the differences in biochemical
composition of flour recovered from the milling of soft and hard grain varieties. An
earlier study by Berliner & Ruter (1928 and 1939), and Mares & Stone (1973) noted
that hard wheat grains fractured along the plane of the endosperm walls, while soft
grained wheats tend to fracture through the cell itself. However, the difference was not
observed with flour recovered from Bühler mill.
96
There have been intensive studies on the optimization of grain shape, size and hardness
for milling, either by adjusting the milling process and recovery (Edwards et al. 2007,
Glenn et al. 1991, Greffeuille et al. 2005, Sharma & Anderson 2004) to these grain
physical properties or through breeding (Barnes 1986, Barnes & Tester 1987, Bhave &
Morris 2008, Gegas et al. 2010, Morris et al. 2005, Morris et al. 2011, Morris et al.
1999, Morrison et al. 1982, Moss et al. 1984, Souza et al. 2002). Various mechanical
tools and biochemical markers have been developed to accurately measure the grain
physical properties and grain fractures by milling. The ACGs were proposed as
biochemical markers for germ contamination of flour, but significant interference from
the cinnamic acid derivatives hindered their application in practice (Barnes & Tester
1987, Edwards et al. 2007, Glenn et al. 1991, Greffeuille et al. 2005, Sharma &
Anderson 2004). In this study, small number of soft grain and hard grain wheats, with
different grain sizes showed significant differences in ACG content and recovery in
flour. Further study using a larger and broader germplasm pool with greater variation in
grain physical properties is required.
Wheat germ and bran tissues, the by-products of milling, are a source of bioactive
compounds such as tocopherols, phytosterols, policosanols, carotenoids, thiamin and
riboflavin besides proteins, sugars, fibre, minerals, and lipids that benefit human health
(Brandolini & Hidalgo 2012, Morrison et al. 1982, Whent et al. 2012). However, they
also contain enzymes that influence noodle colour such as polyphenol oxidase (PPO)
and phenolic compounds (Fuerst et al. 2006a, Fuerst et al. 2006b). Incorporation of
germ and bran tissue into wheat flour following pre-treatment to stabilize and inactivate
the enzymes that influence the end-product quality has been investigated (Ge et al.
2000, 2001). Zhu et al. (2010) reported a positive correlation (R2 = 0.9925) between the
97
yellowness of flour and the amount of defatted wheat germ mixed with Quadrumat
junior mill flour.
5.3.2 Yellowness of YAN and its correlation with lutein and ACG
concentration
Yellowness measured at 0 h for YAN made from Quadrumat Junior flour ranged from
19 - 24 b* units (Table 5.3) and there were significant differences (p<0.001) between
bread wheat cultivars. There was a highly significant correlation between total flour
lutein content and YAN b* 0-24 h, and the correlation (r) reduced with time (Table 5.4).
No significant correlation between total ACG content and YAN b* were observed.
YAN b* increased with time with measurements at 2, 4 and 24 ranging between 22 -29
(Table 5.3). Significant differences (p<0.001) between varieties were maintained. The
increase of b* were significant between 0-2 hours, for all varieties. The increase of b*
between 2-24 hours were not significant for most of the varieties (17 of them). Nine of
the varieties has significantly increased b* between 4-24 hours whilst only 1 variety,
Chara, showed a decrease in b* after 2 hours. The increase in b* between 0-2 hours
coincided with a significant decrease in L* (supplemental material 5.4). This is most
likely a reflection of the negative relationship between L* and b*. The loss of
brightness, or reduction in L*, that occurs in the first few hours after preparation of
YAN has been shown to be associated with rearrangement within the protein matrix that
reduces reflectance rather than any significant chemical change (Asenstorfer et al.
2010) whilst Mares et al. (2001) reported that both lutein and ACG were stable in YAN.
As a confounding effect, dark pigments produced later during storage of YAN
98
(Asenstorfer et al. 2010) may mask the yellow pigments, and thereby reduce b* (Mares
et al. 2001).
5.3.3 Yellow colour developed in the presence of alkaline salts
The difference in yellow colour between YAN and WSN, b* (YAN b*-WSN b*) is
associated with compounds such as the ACGs that turn yellow at the higher pH
produced by the addition of alkaline salt solution. On the other hand, other compounds
such as lutein are yellow in the flour and their yellowness is not pH dependent (Wang
2001). b* ranged between 3.9-7.1 at 0 h, 3-7 at 2 h, 2.7-7.8 at 4 h, and 4.3-8.3 at 24 h
(Table 5.3) and there appeared to be significant differences (p<0.001) between cultivars.
Significant differences between varieties (p<0.001) in b* values were also obtained for
measurement of noodle sheets at these 4 different times. The trends in the change of
b* values between 0 and 24 h were also significantly different between varieties
(p<0.001) (Fig. 5.4).
99
Table 5.3 Yellow colour (b*) of YAN and WSN made from Quadrumat Junior Mill flour and the portion of YAN b* and b*(YAN b*-
WSN b*) developed in the presence of alkaline salt, for 28 bread wheat cultivars at 0, 2, 4 and 24 hour.
Ventura 20.1 + 0.2 22.7 + 0.1 23.4 + 0.1 25.5 + 0.7 14.0 + 0.1 17.6 + 0.1 18.0 + 0.2 18.0 + 0.1 6.1 + 0.3 5.1 + 0.1 5.4 + 0.3 7.6 + 0.7Sunvale 19.9 + 0.2 22.4 + 0.1 22.6 + 0.2 22.5 + 0.2 14.1 + 0.2 16.7 + 0.1 16.5 + 0.1 14.4 + 0.2 5.8 + 0.1 5.7 + 0.1 6.1 + 0.2 8.1 + 0.3Sunco 20.4 + 0.3 23.8 + 0.3 24.5 + 0.2 25.3 + 0.1 14.1 + 0.2 17.1 + 0.1 17.1 + 0.2 17.0 + 0.2 6.3 + 0.3 6.7 + 0.2 7.4 + 0.2 8.3 + 0.3Diamondbird 21.3 + 0.2 23.7 + 0.1 23.9 + 0.1 24.2 + 0.2 15.1 + 0.1 18.5 + 0.1 19.1 + 0.1 18.8 + 0.1 6.2 + 0.3 5.3 + 0.2 4.8 + 0.1 5.4 + 0.2Sunlin 20.4 + 0.2 23.4 + 0.1 23.8 + 0.1 24.0 + 0.2 15.3 + 0.2 19.0 + 0.2 19.1 + 0.2 18.1 + 0.1 5.1 + 0.3 4.5 + 0.3 4.6 + 0.3 5.9 + 0.3Cunningham 21.2 + 0.1 23.6 + 0.1 24.0 + 0.1 23.8 + 0.1 14.5 + 0.3 17.9 + 0.2 18.1 + 0.1 17.6 + 0.1 6.7 + 0.4 5.7 + 0.3 5.8 + 0.2 6.3 + 0.2EGA Gregory 21.7 + 0.2 24.8 + 0.3 25.5 + 0.3 26.8 + 0.2 15.6 + 0.2 19.2 + 0.1 19.5 + 0.2 19.8 + 0.1 6.1 + 0.3 5.7 + 0.3 6.1 + 0.5 7.0 + 0.3Hartog 21.1 + 0.1 23.7 + 0.2 24.0 + 0.2 24.0 + 0.2 14.4 + 0.2 18.1 + 0.1 18.6 + 0.1 18.1 + 0.1 6.7 + 0.2 5.6 + 0.2 5.4 + 0.2 5.9 + 0.2Janz 20.9 + 0.2 23.1 + 0.2 23.5 + 0.2 23.3 + 0.2 14.8 + 0.1 17.7 + 0.1 17.9 + 0.2 17.5 + 0.1 6.1 + 0.2 5.5 + 0.2 5.5 + 0.3 5.8 + 0.3EGA Hume 21.2 + 0.3 23.6 + 0.1 24.1 + 0.2 24.5 + 0.2 15.0 + 0.1 18.1 + 0.1 18.3 + 0.1 18.3 + 0.2 6.1 + 0.3 5.5 + 0.2 5.8 + 0.1 6.2 + 0.3Kennedy 21.5 + 0.3 24.0 + 0.1 24.4 + 0.1 24.1 + 0.1 14.4 + 0.1 17.9 + 0.1 18.2 + 0.1 18.1 + 0.2 7.1 + 0.3 6.1 + 0.1 6.2 + 0.1 6.1 + 0.2Lang 20.2 + 0.2 24.1 + 0.3 25.0 + 0.3 25.1 + 0.6 14.1 + 0.2 17.0 + 0.2 17.1 + 0.2 17.2 + 0.2 6.2 + 0.4 7.0 + 0.4 7.8 + 0.5 7.9 + 0.6Batavia 22.3 + 0.3 25.5 + 0.3 25.9 + 0.2 26.3 + 0.2 16.7 + 0.1 20.1 + 0.1 20.3 + 0.2 20.4 + 0.3 5.5 + 0.2 5.4 + 0.4 5.6 + 0.4 5.9 + 0.4Baxter 20.2 + 0.2 22.7 + 0.1 22.9 + 0.1 23.0 + 0.2 13.9 + 0.1 17.4 + 0.2 17.2 + 0.2 15.5 + 0.2 6.2 + 0.2 5.3 + 0.2 5.7 + 0.1 7.5 + 0.2Spear 21.7 + 0.2 24.1 + 0.1 24.2 + 0.2 24.7 + 0.4 15.5 + 0.2 18.3 + 0.2 18.4 + 0.3 17.9 + 0.2 6.2 + 0.4 5.8 + 0.3 5.8 + 0.4 6.8 + 0.6Frame 20.8 + 0.4 24.2 + 0.2 25.0 + 0.2 26.1 + 0.3 15.7 + 0.2 19.7 + 0.1 19.7 + 0.1 19.1 + 0.2 5.1 + 0.5 4.6 + 0.3 5.3 + 0.2 7.1 + 0.3Halberd 21.1 + 0.1 23.7 + 0.1 24.3 + 0.1 25.1 + 0.2 16.2 + 0.1 18.7 + 0.1 19.2 + 0.2 18.3 + 0.1 4.9 + 0.1 5.0 + 0.2 5.1 + 0.2 6.8 + 0.3Krichauff 23.5 + 0.5 27.0 + 0.4 27.8 + 0.4 29.3 + 0.3 19.6 + 0.2 23.2 + 0.4 24.5 + 1.0 22.5 + 0.2 3.9 + 0.4 3.9 + 0.2 3.4 + 0.9 6.8 + 0.3Kukri 20.2 + 0.2 23.1 + 0.2 23.8 + 0.2 25.4 + 0.5 16.0 + 0.2 19.3 + 0.0 19.3 + 0.1 18.3 + 0.1 4.2 + 0.3 3.8 + 0.2 4.5 + 0.3 7.2 + 0.5Chara 21.3 + 0.2 23.8 + 0.2 23.8 + 0.2 22.9 + 0.2 16.3 + 0.3 19.7 + 0.1 19.5 + 0.1 18.7 + 0.1 5.0 + 0.4 4.2 + 0.2 4.3 + 0.1 4.3 + 0.2Meering 21.5 + 0.3 24.6 + 0.3 24.8 + 0.3 24.3 + 0.2 16.5 + 0.2 19.6 + 0.2 19.8 + 0.1 18.9 + 0.1 5.1 + 0.3 5.0 + 0.4 5.0 + 0.4 5.4 + 0.2Silverstar 21.4 + 0.3 24.5 + 0.2 24.8 + 0.1 24.4 + 0.2 15.5 + 0.7 17.8 + 0.1 18.0 + 0.1 17.5 + 0.2 5.9 + 0.5 6.7 + 0.2 6.9 + 0.2 6.9 + 0.3Annuello 21.7 + 0.2 25.0 + 0.1 25.1 + 0.1 24.7 + 0.1 15.6 + 0.1 18.8 + 0.1 19.0 + 0.2 18.1 + 0.2 6.1 + 0.2 6.2 + 0.2 6.1 + 0.1 6.7 + 0.2GBA Ruby 19.7 + 0.1 22.6 + 0.2 22.9 + 0.1 23.3 + 0.1 13.5 + 0.2 16.4 + 0.1 16.6 + 0.1 16.5 + 0.1 6.2 + 0.2 6.3 + 0.2 6.4 + 0.2 6.7 + 0.2Cascades 22.5 + 0.2 24.9 + 0.3 25.1 + 0.2 24.3 + 0.2 18.2 + 0.3 21.1 + 0.2 21.1 + 0.1 18.7 + 0.5 4.3 + 0.3 3.9 + 0.2 4.0 + 0.1 5.6 + 0.5Carnamah 21.8 + 0.4 23.3 + 0.2 23.1 + 0.2 22.8 + 0.3 17.7 + 0.3 20.3 + 0.2 20.4 + 0.3 17.8 + 0.3 4.1 + 0.4 3.0 + 0.3 2.7 + 0.4 5.1 + 0.5Reeves 20.5 + 0.2 23.6 + 0.1 23.8 + 0.2 24.1 + 0.1 14.5 + 0.2 17.9 + 0.1 18.2 + 0.1 19.3 + 0.1 6.0 + 0.1 5.8 + 0.2 5.6 + 0.2 4.7 + 0.2Westonia 23.0 + 0.3 25.6 + 0.1 25.7 + 0.1 25.9 + 0.2 17.6 + 0.2 20.9 + 0.2 21.4 + 0.1 20.2 + 0.1 5.4 + 0.2 4.6 + 0.1 4.4 + 0.2 5.6 + 0.2MaxMinMeans 21.2 + 0.2 24.0 + 0.2 24.3 + 0.2 24.6 + 0.3 15.5 + 0.3 18.7 + 0.3 18.9 + 0.3 18.2 + 0.3 5.7 + 0.16 5.3 + 0.2 5.4 + 0.2 6.4 + 0.2
27.822.6
29.322.5 3.0 2.7 4.3
b*(YAN b*-WSN b*)2 4 24
7.0 7.8 8.316.4 16.5 14.4
WSN b*0
YAN b*Cultivars 2 4 24
19.723.5
0
7.13.9
0
19.613.5
2 4 24
23.2 24.5 24.027.022.4
100
Table 5.4 Correlation between total lutein content and ACG content in flour with YAN
b* and b* (YAN b*-WSN b*). # signifies the significant correlations.
Figure 5.4 The trends of b* values between 0 to 24 hours measurements for varieties
that showed significant differences (p<0.001).
Yellowness (b* and b*)
Time of measurement Total lutein Total ACG
0 hours #0.821 0.1262 hours #0.749 0.1064 hours #0.666 0.032
24 hours #0.497 -0.1100 hours # -0.731 -0.4542 hours #-0.675 -0.2244 hours #-0.724 -0.266
24 hours -0.380 -0.342
b* of YAN
b* (b*YAN-b*WSN)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
0 2 4 24
b* (YAN-WSN)
Hours of b* measurements
Sunvale
Sunco
Krichauff
GBA Ruby
Carnamah
Reeves
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Flour ACG content and YAN b* at 0, 2 or 24 hours were not significantly correlated
(Table 5.3). Although it seems clear that ACGs can contribute to the yellow colour of
alkaline noodles (Asenstorfer et al. 2006), ACG content did not influence the
differences in intensity of the yellow colour between varieties. This may be a reflection
of the relatively narrow range in flour ACG content, 11-28 g/g (Tables 5.1 and 5.3)
compared with the difference in ACG content required to produce a significant change
in b*. It would appear that cultivars with wider range of ACG content in the flour and
b* value would be required to make a significant impact on YAN b*. From the
survey of genetic variation in ACG content and composition (Chapter IV), the range of
total ACG content in whole grain is 42.8 to 166.6 g/g (Table 4.1). Similarly, in this
experiment, total grain ACG content ranged from 42.8-109.2 g/g but only 11.4-28.4
g/g was recovered in the flour (Table 5.1). The lack of correlation between the ACG
content in the grain and in the flour suggests that the amount of ACG in the flour is not
determined by the content in the grain, but by milling.
The strong negative correlation between lutein content and b* at 0-4 h, but not at 24 h,
is difficult to explain since there is no evidence in the literature that change in pH
affects the absorption of lutein in the visible region of the spectrum. It is possible that
this result is an artifact due to the specific characteristics of the varieties selected for
this study as representing the range in ACG and lutein content. In particular, a closer
examination of the results indicated that the correlation was largely due to high lutein
varieties such as Krichauff developed in southern Australia and not selected for YAN
quality. In comparison, there was no significant correlation between lutein
concentration and b* for a subset of varieties developed in northern NSW and
Queensland where there is a strong focus on YAN.The lack of positive correlation
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between the increase of b* from 0 to 24 hours and the pigment content suggests that
lutein and ACGs contribute to yellow colour of noodles at 0 hour, but that the increase
in b* with time after alkaline solution addition has nothing to do with these two yellow
pigments but are possibly influenced by a complex interaction involving the time-
dependent darkening of noodles. The initial darkening (Asenstorfer et al. 2010),
involves a physical change in the noodle sheet that results in a reduction of reflectance.
Beyond 2-4 h, production of dark pigments (from both PPO and non-PPO reactions)
occurs, which have the effect of masking yellow pigments (supplemental material 5.4)
(Mares et al. 2001). The noodles appear darker and more yellow. The amount of
darkening due to these reactions varies with both variety and environment. Both lutein
and ACG are stable in YAN (Mares et al. 2001), the yellow colour is already present,
lutein, or generated immediately upon the addition of alkali, ACG, and there appears to
be no reason to suggest that the colour yield of either should change with time. As a
result the data obtained at 0 h is likely to be the best estimate of the specific
contribution of these pigments to the colour of noodles and the data collected at 2-24h is
likely to be confounded by other factors.
5.3.4 Prediction of the contribution of ACG to b* (YAN-WSN)
In the absence of a supply of authentic ACG, a standard curve was constructed by
adding known amounts of rutin, an apigenin-C-glycoside with the same chromophore as
ACG, to flour prior to the preparation of YAN (Fig. 5.2). With increasing amount of
rutin, Δb*(YAN with rutin – YAN control) initially increased linearly but then the
increase in Δb* became progressively less per unit increase in rutin. Curves for
Δb*(YAN with rutin – YAN control) determined at 0, 2 and 4 h were similar and
significantly greater than for measurements taken at 24h. By using Δb* from YAN with
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rutin – YAN control, little effect of darkening would be expected, since it should be
similar in YAN with rutin and YAN control, unless rutin itself is contributing to the
darkening.
Based on the standard curve, the predicted contribution of flour ACG concentrations of
11.4-28.4 g/gtoYb* would be 1.0-3.0 and 0.8-1.7 respectively depending on
whether the curves at 0-4 h or 24 h are used. By comparison, if all the ACG present in
grain (Chapter IV), 42.8 to 166.6 g/g, could be recovered in flour the contribution to
YAN b* would be 3.5-11.9 for 0 to 4 h and 2.4-5.4 for 24 h. The ACG concentration in
the grains of cultivars used in the Quadrumat milling experiments ranged from 42.8-
109.2 g/g, would be equivalent to increases in YAN b* of 3.5-9.0. There is potential to
increase the b* value by selecting cultivars with higher ACG content in the grain and
by also considering recovery during milling. There is also potential perhaps to achieve
the increase in b* of YAN by mixing stabilized germ back into flour after milling.
Further study is required to explore this possibility.
5.3.5 Contribution of ACG to b*(YAN –WSN)
The predicted contribution of ACG to YAN b*, mean at 0, 2 or 4 h of 1.6 – 2.1 (Table
5.5), was significantly less than the observed values of b* (YAN-WSN), 5.3 – 5.7
(Table 5.3). This difference between the predicted and actual measurements indicates
the presence of other factors that influence the yellow colour of alkaline noodles.
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Figure 5.5 Standard curve relating change in YAN b* (b* = b*YAN with rutin –
b*YAN control) to the amount of added rutin (a flavone glycoside) at 0, 2, 4, and 24.
Green: b* at 0 hours, black: 2 hours, red: 4 hours, and blue: 24 hours.
b of YAN
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Table 5.5 The predicted values for b* of YAN sheets made from grain of 28 cultivars
of bread wheat milled by Quadrumat Junior Mill, based on rutin-b* standard curve
(Figure 5.2).
5.4 Conclusions
ACGs make a small contribution to the yellow colour of alkaline noodles (YAN), but
explain only a part of the yellow colour that develops specifically in the presence of
alkaline salts. Possibly due to a combination of this small contribution, the limited
variation in ACG concentration between cultivars, and the relatively limited variation in
Δb*(YAN – WSN), no correlation between flour ACG concentration and YAN b* or
0 hours 2 hours 4 hours 24 hours36.4x/(406.4 + x) 31.2x/(271.5 + x) 26.2x/(241.3 + x) 9.7x/(133.7 + x)
Ventura 15.5 1.3 1.7 1.6 1.0Sunvale 14.4 1.2 1.6 1.5 0.9Sunco 15.8 1.4 1.7 1.6 1.0Diamondbird 11.4 1.0 1.3 1.2 0.8Sunlin 17.3 1.5 1.9 1.8 1.1Cunningham 18.0 1.5 1.9 1.8 1.2EGA Gregory 13.3 1.1 1.5 1.4 0.9Hartog 17.1 1.5 1.9 1.7 1.1Janz 20.0 1.7 2.1 2.0 1.3EGA Hume 18.8 1.6 2.0 1.9 1.2Kennedy 16.8 1.4 1.8 1.7 1.1Lang 19.1 1.6 2.0 1.9 1.2Batavia 14.8 1.3 1.6 1.5 1.0Baxter 16.1 1.4 1.7 1.6 1.0Spear 16.9 1.5 1.8 1.7 1.1Frame 18.8 1.6 2.0 1.9 1.2Halberd 24.6 2.1 2.6 2.4 1.5Krichauff 20.8 1.8 2.2 2.1 1.3Kukri 21.0 1.8 2.2 2.1 1.3Chara 18.4 1.6 2.0 1.9 1.2Meering 28.4 2.4 3.0 2.8 1.7Silverstar 25.1 2.1 2.6 2.5 1.5Annuello 21.4 1.8 2.3 2.1 1.3GBA Ruby 22.2 1.9 2.4 2.2 1.4Cascades 20.9 1.8 2.2 2.1 1.3Carnamah 27.4 2.3 2.9 2.7 1.7Reeves 26.6 2.2 2.8 2.6 1.6Westonia 20.0 1.7 2.1 2.0 1.3Max 28.4 2.4 3.0 2.8 1.7Min 11.4 1.0 1.3 1.2 0.8Means 19.3 1.6 2.1 1.9 1.2
CultivarsTotal ACG
(g/g)
b* of YAN
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Δb* was observed. Unfortunately much of the grain ACG is discarded during the
milling process and there appears to be little prospect of significantly increasing the
proportion of grain ACG recovered in flour.
Given the low contribution of ACGs to YAN yellowness, this compound might not be a
target that would be of interest to the breeders. However, in this study, further
possibilities and efforts to increase the ACG recovery in the flour and their contribution
to the yellowness of YAN were explored, further examined and discussed.
Bühler milling improved flour recovery and the amount of ACG recovered in the flour
for 3 out of 10 varieties, but these improvements were not significant and not enough to
achieve the yellowness of commercial noodles containing additives (b*= + 45). It would
required greater than 500 mg/g ACG to achieve this b* value. In addition, the
percentage of ACG recovered in the Bühler flour is generally less to that of Quadrumat
milling. Based on this observation it appears unlikely that recovery of ACG in flour in a
commercial mill would be significantly different. The recovery of ACG in mill flour is
strongly influenced by their location in the outer parts of the grain (grain coat and
embryo tissues) which are discarded during milling as bran and pollard respectively.
The efficiency of removal of these parts from the starchy endosperm during milling is
influenced by the grain softness/hardness and moisture pre-conditioning.
Cultivars with substantially higher grain ACG concentration that give a much higher
recovery in flour are required for improvement of YAN b*. The ACG content in wheat
grain still showed potential for improvement of ACG concentration in flour but the
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physical properties of the grain need to be improved for a better milling recovery.
Further study involving germplasm with wider variation in the grain physical properties
is required in order to relate these physical and the ACG traits. Moreover, as there was
variation in ACG recovery in the flour after grain milling, further study is required to
explore this potential in relation to the possibility to achieve the increase in b* of
YAN by mixing defatted or stabilized wheat germ back into flour after milling.
The results in this experiment also indicated the presence of unknown pigment
compound(s) in addition to ACGs that contribute to the yellowness of YAN. Further
research is required to determine the structure and tissue location of these compounds in
relation to their recovery from grain milling.
In comparison with lutein, the ACGs are present in higher concentration in grain and
flour but their contribution to yellowness of YAN is much lower than lutein. Due to its
presence in starchy endosperm, an increase in lutein concentration could deliver
substantially higher YAN b*. In the current market environment this may be
unacceptable since the yellow flour would be undesirable in products other than YAN.
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Chapter VI: QTL associated with Apigenin di-C-glycoside
(ACG) concentration and composition in bread wheat
(Triticum aestivum L.) grain
and identification of candidate genes
6.1 Introduction
Glycosylation reactions like those responsible for the synthesis of apigenin di-C-
glycosides (ACG) have important roles in modification and diversification of
metabolites that are involved in various functions from structure and storage to
signalling in plants (Breton et al. 2006). However, despite their diverse and important
roles the genetic control of the ACG biosynthesis pathway, a side branch in the
flavonoid pathway, in cereals is not well understood.
Following conversion of naringenin chalcone to 2S-naringenin flavanone by chalcone
isomerase (CHI), the first committed step towards ACG synthesis appears to involve the
formation of the hemiketal form of the flavanone by flavanone 2-hydroxylase (F2H).
The hemiketal ring structure then opens prior to C-glycosylations which lead to the
formation of 2 sets of Wesseley-Moser isomers containing arabinose and glucose
(ACG1) or arabinose and galactose (ACG2). The reactions that follow the C-
glycosylation are similar for both ACG1 and ACG2. Chalcone and flavanone are also
precursors for the biosynthesis of other metabolite in flavonoid biosynthesis (Grotewold
et al. 1998, Shirley 2001).
112
In the earlier part of this study, a survey of 67 bread wheat cultivars and related species
confirmed the presence of genetic variation in ACG concentration and composition as
previously reported by Asenstorfer et al. (2006). The results for the CS nullisomic-
tetrasomic together with the frequency distribution of ACG content and ratio traits in
the set of varieties and related species suggested that concentration and ACG1/ACG2
ratio may be controlled by multiple loci and a single locus respectively. It is not clear
whether the synthesis of ACG1 and ACG2 involves a glycosyltransferase that is capable
of utilizing both UDP-glucose and UDP-galactose or glycosyltransferases that are
specific to each of these sugar nucleotides. Both C-glucosylation and C-galactosylation
reactions contribute in a coordinated manner to the total concentration and ratio of
ACGs. However, although there was more ACG2 than ACG1 in the grain of most of the
cultivars surveyed, variation in the ratio appeared to be due to an alteration in C-
glucosylation. Further molecular and enzymatic studies are required to investigate the
variation in availability of the sugar molecules and C-glycosyltransferase activity.
Only limited information is available on the biochemistry and molecular biology of C-
glycosylation from previous work. Brazier-Hicks et al. (2009) reported a C-
glucosyltransferase gene specific for UDP-glucose in rice. Du et al. (2010) and Du et al.
(2009) reported that F2H genes in rice and sorghum code for the enzyme that provides
the substrate for the C-glucosylation reaction. However, no information is available on
such genes in wheat. In addition, there are two other enzymes that have been studied in
wheat and other crops, UDP-glucose 4-epimerase (Zhang et al. 2006) and a UDP-
glucose transporter (Bowsher et al. 2007, Muaoz et al. 1996), which might also be
involved in providing sugar molecules for the C-glycosylation reaction. It should be
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noted here that these sugar nucleotides are also required for several other pathways, and
no information on their contribution to C-glycosylation has been reported.
Gene discovery in hexaploid bread wheat has been facilitated by genetic mapping. This
approach involves generating the genetic linkage map of the experimental populations
using RFLP, AFLP, SSR and SNP markers, or takes advantage of their existing genetic
linkage maps. Preliminary QTL analysis detects the regions for fine mapping that is
required to capture candidate gene sequences from syntenic regions of chromosomes in
other grass species or from BAC clones. The availability of nullisomic-tetrasomic,
ditelosomic and substitution lines of Chinese Spring aid this approach if the trait of
marker is present in the Chinese Spring euploid, to confirm the chromosome location of
the traits or new markers.
The aims of this study were to validate QTL associated with variation for ACG
concentration and ACG1/ACG2 ratio in bread wheat grain, to add more markers to the
QTL region and reduce the size of the chromosome interval involved, and to identify
candidate gene(s) linked with these traits. It is anticipated that this information will
provide further insight into the mechanisms involved in ACG biosynthesis in bread
wheat and provide molecular tools required for manipulation of these traits in breeding
programs.
6.2 Material and methods
6.2.1 Plant material
A sub-set of a Sunco x Tasman doubled haploid population developed by (Kammholz et
al. 2001) consisting of 153 lines and 361 markers (section 3.2.3.2) was used for the
114
initial mapping and QTL analysis. Subsequently, a larger set of 275 doubled haploid
lines was used for the fine mapping. For the preliminary polymorphism screening of
new SSR markers, a panel of Sunco/Tasman doubled haploid lines (10 lines with ratio
phenotype similar to Sunco (high ratio) and 10 similar to Tasman (low ratio) (section
3.2.3.3) were used. The group 7 nullisomic-tetrasomic lines and ditelosomic lines of
Chinese Spring 7 (section 3.2.2 and section 3.2.3.2) were used to confirm the
chromosome arm locations and to get genome sequences for designing SNP markers
(section 6.2.3.3 SNP marker analysis).
6.2.2 Validation of the QTL associated with variation in ACG
composition, ACG concentration, and 100 grain weight in the
Sunco/Tasman
6.2.2.1 Construction of new genetic maps for Sunco/Tasman incorporating
additional markers
The genetic map of the 153 lines Sunco/Tasman doubled haploid population was re-
constructed with 361 markers using Mapdisto 1.7.5. b4 2007 version and GENSTAT
(version 14 (Chapter 3 section 3.4.2.2). Markers were ordered within each linkage
group and distances between markers computed using Mapdisto 1.7.5. b4 2007 version.
The distances in the map were then confirmed with GENSTAT 14) before the QTL
analyses were performed. Using GENSTAT software, the linkage groups were re-
constructed with a 0.365 recombination factor and optimising the clustering with 0.5
penalty for each missing data point. The results were saved in a QTL save structure and
then exported and viewed in Flapjack (Plant Bioinformatic Group, The James Hutton
Institute) to check for errors and double recombination. The complete set of
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chromosome maps was drawn using MapChart 2.2 (Plant Research International,
Wageningen Agricultural University, The Netherlands).
6.2.2.2 QTL analyses of ACG concentration, ACG composition and 100
grain weight.
The results of an initial QTL analysis of Sunco/Tasman doubled haploid population by
Willsmore and Mares (unpublished data) for ACG concentration, total ACG content and
ACG ratio using MapManager QTX software were confirmed in the new analysis
performed in GENSTAT 14. Details on the data sets used in this analysis are available
in the general method section. In addition, QTL analysis for 2 other traits, the ACG1
and ACG2 content were also performed with the same method. The genetic predictors
of doubled haploid (DH1) population were calculated according to the Kosambi
function, at marker positions (by default) and between markers (every 10 and 20 cM).
Single trait linkage analysis (Single environment) was performed for 100 grain weight,
ACG concentration and ACG composition. The QTL for ACG1/ACG2 ratio was also
analysed as a binary trait (0/1), while the other traits were treated as quantitative traits.
Significant thresholds were set up as default (=0.05), based on a Bonferroni correction
as described by (Li & Ji 2005). The initial genome-wide scans were performed (Simple
Interval Mapping, SIM) to obtain candidate QTL positions. The QTL effects were
estimated by Composite Interval Mapping (CIM) using the candidate QTLs detected in
the initial scan by SIM as cofactors. The minimum cofactor proximity and minimum
separation for selected QTLs were set at 30 cM and 10 cM respectively. REML
variance component analyses were performed by fitting the genotype factor as a random
model. The fitting of QTL into the fixed model were assessed by Wald statistic and F
statistic (Fpr<0.001). The final set of QTL positions and effects were estimated by
116
fitting the final QTL model following backwards selection from a set of candidate
QTLs. The result of Wald statistic or the probability value on a -log10 scale then were
plotted to produce the map. The results were saved in a QTL save structure and
exported and viewed in Flapjack (Plant Bioinformatic Group, The James Hutton
Institute). These steps followed the example outlined in (Malosetti et al. 2011).
The effects of QTL detected for each ACG trait were further examined by determining
the interaction between the QTL. The lines of Sunco/Tasman doubled haploid
population were grouped into marker allele classes according to the genotypes of the
closest markers. The analyses were performed by Mixed Models (REML variance
components analysis) in GENSTAT 14 with markers and marker interactions as fixed
model and the number of lines in each marker genotype group as random model.
Epistasis was detected by significant marker interactions at Fpr <0.001.
Multi-trait linkage analysis (single environment) was performed for chromosome 7B for
the concentration and content per grain of ACG1 and ACG2 (g/g and g/grain); and
for the ACG1/ACG2 ratio. Similar analysis was also performed for chromosome 4B for
the total ACG (g/g and g/grain), ACG1 and ACG2 to obtain a final set of estimated
QTL effects.
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6.2.3 Addition of markers to the major QTL for ACG concentration and
composition located on 7BS
6.2.3.1 DNA Isolation
The DNA was extracted using a mini prep ball bearing DNA extraction protocol
(Karakousis & Langridge 2003). Each leaf sample was placed in a screw cap tube
together with 1 large (9 mm) and 3 small ball bearings. The tubes then were frozen in
liquid nitrogen for 5 minutes and then placed on a shaker for 1 minute to grind the leaf
tissue to a fine powder. After the ball bearings were removed, the samples were thawed
at room temperature for 2-5 minutes. Then, 700 L extraction buffer was added to the
samples, followed by addition of 700 L phenol/chloroform/iso-amyl alcohol (25:24:1).
After mixing well, the extracts were transferred into silica matrix tubes and spun at
4000 rpm for 10 minutes. A second phenol extraction was done and the upper aqueous
phase transferred to eppendorf tubes. The samples were then washed by adding 60 L
of 3M sodium acetate pH 4.8 and 600 L isopropanol. The tubes were inverted to
precipitate the DNA. After centrifugation at 13000 rpm for 5 minutes, the supernatant
was poured off and the remaining pellet was washed again with 70% ethanol and then
centrifuged for 2 minutes at 13000 rpm. After the ethanol was removed, the samples
were air-dried. The pellet obtained was resuspended in 50 L of RNAse at 4oC
overnight and then stored at -20oC.
6.2.3.2 SSR marker analysis
Polymorphism test
DNA samples from a panel of 20 Sunco/Tasman lines (section 3.2.3) and 2 DNA
samples of each of the parents were used for the initial SSR marker polymorphism test.
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68 SSR markers that had previously been mapped on 7B chromosome between
gwm400-wmc76 and wmc76-gwm573 in wheat genetic maps of various populations in
CMap databases (Genica, Grain Genes, CYMMYT databases), 7BS1-0.27-1.00 and
C7BS1-0.27 bins of deletion map (Sourdille et al. 2004b) and published maps (Boyko et
al. 1999, Carter et al. 2009, Crossa et al. 2007, Emebiri et al. 2010, Gupta et al. 2002, Li
et al. 2008, Lin et al. 2008, Liu et al. 2005, Panfili et al. 2004, Quarrie et al. 2005,
Schnurbusch et al. 2004, Shermana et al. 2010, Song et al. 2005, Sourdille et al. 2003,
Sourdille et al. 2004a, Sourdille et al. 2004b, Uphaus et al. 2007, Xue et al. 2008, Zhang
et al. 2008) were chosen for this test.
The analysis was performed by multiplex PCR according to (Hayden et al. 2008a,
Hayden et al. 2008b). Marker binning information was drawn from Genica database and
Automated Designer for Genetic Analysis was used to design the PCR analyses. The 7
L PCR reaction contained 0.2mM dNTP, 1x Multiplex Ready Buffer, 75 nmol dye
labelled tagR and tagF primers (vic, fam, ned, pet), 50ng genomic DNA, 0.175U
Immolase DNA polymerase (Kit from Bioline), optimal concentration of locus specific
primers as determined in uniplex assays and water. PCR condition was as follows:
denaturation at 94oC for 2 minutes, 4 cycles of: 92oC for 30 seconds, 50oC for 1:30
minutes, and 72OC for 1 minute, 19 cycles of: 92oC for 30 seconds, 63oC for 1:30
minutes and 72oC for1 minutes, 39 cycles of: 92oC for 15 sec, 54oC for 1 minute, 72oC
for1 min, final extension of 72oC for 10 minutes. Visualization of the PCR products was
performed by GelScan2000 (Corbett Research) and ABI3730 DNA analyser (Applied
Biosystems). SSR allele sizing and polymorphism analysis were performed
automatically using GeneMapper v3.7 software (Applied Biosystems).
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Mapping polymorphic markers in the Sunco/Tasman doubled haploid population
Thirty seven polymorphic SSR markers were assayed on each of 275 lines of the
Sunco/Tasman population.
6.2.3.3 Single nucleotide polymorphism (SNP) marker analysis
Source of SNPs
Six expressed sequence tags (EST) sequences from chromosome 7B of wheat
containing SNPs that are polymorphic in Sunco and Tasman parents and with
homologous sequences in rice chromosome 6 and 8 (Sorrells et al. 2003) and
Brachypodium distachyon chromosome 1 and 3 (ModelCrop database) were used to
align the respective maps (Table 6.1). Information on these 6 single nucleotide
polymorphisms (SNPs) was obtained from Dr. Matt Hayden, Victorian DPI (pers.
com.). Information on the genome specific primer pairs (GSP) flanking these SNPs
were drawn from Wheat SNP databases
(http://wheat.pw.usda.gov/SNP/new/index.shtml). The lists of wheat EST sequences
were drawn from wEST-SQL databases (http://wheat.pw.usda.gov/wEST/).
SNP marker analysis
Genome-specific primer pairs (GSP, Table 6.1) were used to amplify SNP-containing
regions from DNA samples representing the panel of Sunco/Tasman doubled haploid
lines and from nullisomic-tetrasomic and ditelosomic lines of Chinese Spring.
Touchdown PCR conditions were optimized for each pair. The PCR products were then
separated on 1% agarose gel stained by SYBR safe and the bands that were present in
Sunco and Tasman and absent in nulli 7B lines were then purified from the gel using
Illustra Gel Purification Kit and sequenced using the GSPs. The sequences obtained
120
were analysed by Vector NTI Advance version 11 to identify the SNP and design the
assay.
A temperature switch PCR (TSP) method described by Tabone et al. (2009) was used to
analyse the polymorphism of the SNP markers in the 275 lines of the Sunco/Tasman
doubled haploid population. The amplification was performed using a pair of locus
specific primers (LSP) and a pair of allele specific primers (ASP) that were designed as
explained by Hayden et al. (2009) and Hayden et al. (2010). Non-complementary
nucleotides at 5‟ terminal were included in the LSPs to increase the Tm from 43-47oC
(optimum 45oC) to 52-55oC (optimum 53oC) while the ASPs were designed with Tm of
60-65°C (optimal 63°C).
The PCR was performed in a 4 μl reaction containing 1× PCR buffer (16 mM
(NH4)2SO4, 0.01% Tween-20, 100 mM Tris-HCl, and pH 8.3, Bioline), 1.5 mM MgCl2,
100 ng/μl bovine serum albumin, 0.2 mM dNTP, 0.1 μM each of forward and reverse
LSP primer, 0.5 μM of forward and reverse ASP primer (unless otherwise stated), 0.15
U Immolase (Bioline) and between 10-50 ng dried down genomic DNA. The PCR
condition is as follows: denaturation step at 95°C for 3 minutes, first reaction phase of
TSP amplification for a total of 35 cycles with 15 cycles of 95°C for 30 seconds, 58°C
for 30 seconds, 72°C for 60 seconds to enrich the target locus harboring the SNPs, and
the second reaction phase consisted of 5 cycles of 95°C for 10 seconds and 45°C for 30
seconds, followed by 15 cycles each consisting of 95°C for 10 seconds, 53°C for 30
seconds and 72°C for 5 seconds. The PCR products were visualized on a 1% agarose
gel with SYBR safe staining.
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Table 6.1 Wheat EST sequences from chromosome 7B of wheat with homologous sequences in rice (chromosome 6 and 8) and
Brachypodium distachyon (chromosome 1and 3) and their genome specific primer (GSP) sequences (Wheat SNP database, USDA).
Chromosome Position (bp) Chromosome Position (bp) Forward primer Reverse primerBE352570 6 9,092,387-9,092,877 (+) 1 41,582,446-41,582,925 (+) CAGATCATCCCGTGGAACTT CGAAACCAGAAACGATGTTGBE445287 8 25,520,556-25,522,082 (+) 3 42,791,581-42,793,820 (+) GGGCATGTGTCAAGGGC TTCCCATGAAGAGGTGGTTC
8 25,651,324-25,652,211 (+)6 30,377,762-30,378,989 (+) 3 4,026,222-4,026,253 (+)
BE518436 6 30,377,762-30,378,989 (+) 1 30,748,109-30,750,751 (+) ATGTCCTTGGAAACTTCCCC GACCATGTCTAACAGTAAAACBF201699 8 24,333,334-24,334,474 (+) 3 41,571,060-41,571,361 (+) GAAGGGTTTGTGTGGACGAT TAATCCTTCCAATAATATGATGTAG
24,463,463-24,464,603 (+) BQ169669 8 27,267,082-27,268,137 (+) 3 43,867,506-43,868,726 (+) GAATTGCAGCCTTAAATGGG ACTCTTATTTTCATCTCTGG
27,397,211-27,398,266 (+)BQ171683 6 24,579,353-24,579,453 (+) 1 31,562,280-31,563,491 (+) GTCTCCCAAATTACGAACTTC GGAGCTTGATGATAACCGGA
Wheat EST
Position in Rice (bp) Position in Brachypodium distacyon (bp) Genome specific primer (GSP)
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6.2.3.4 Apigenin-C-diglycoside analysis
ACGs were analysed as previously described in section Chapter 3 section 3.4.1.1 and
the values of ACG concentration and composition were calculated as in section Chapter
3 section 3.4.2.1. Hundred grain weight was measured as in section Chapter 3 section
3.4.1.3.
Genetic analysis of ACG trait data was performed using GENSTAT 14. Differences
between parent lines were analysis by one way ANOVA with the parent lines as
treatment factors. Significant differences were identified at p<0.05. The distribution of
ACG traits in the 275 lines of the Sunco/Tasman population were tested against
Gaussian normal distribution using similar software.
6.2.3.5 Linkage mapping and QTL analysis
The marker scores were analysed for segregation in the population by chi-square
analyses (GENSTAT 14). Only 13 new markers that showed no distortion were added
to the revised map. These new markers were ordered by MapDisto Genetic Software
version 1.7.5 Beta 4 for MS windows 2007 (Mathias Lorieux, Institut de Recherche
pour le development, (IRD, France) and International Centre for Tropical Agriculture
(CIAT-CGIAR, Colombia).
The QTL analyses for ACG component traits were performed using GENSTAT 14 as
mentioned in section 6.2.2.2. The QTL for ACG1/ACG2 was also re-analysed as a
binary trait with 0.8 as the critical value; ratio above 0.8 similar to Sunco, while ratio
below 0.8 similar to Tasman (Supplemental materials 3.5). This QTL analyses of the
ACG traits as binary traits were not performed with other traits because the distributions
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of the traits in the populationwere continuous and there was no distinct separation
between the high and low value of the traits as there was with the ratio traits.
Comparison of 7BS of Sunco/Tasman with other wheat maps
The Sunco/Tasman genetic map of 7BS was compared with other physical, genetic and
consensus maps for wheat in CMap databases (Graingenes
(http://wheat.pw.usda.gov/GG2/index.shtml), Genica
(http://www.genica.net.au/index.php/GENica), KomugiMap
(http://map.lab.nig.ac.jp:8080/cmap/), Gramene (www.gramene.org), CYMMYT
(http://cmap.cimmyt.org)). Full sequences of wheat ESTs containing the SNPs were
obtained from Wheat Genomic Sequence database (cerealsDB.uk.net), while the ESTs
and SNPs information was obtained from Wheat SNP databases
(http://wheat.pw.usda.gov/SNP/new/index.shtml). The assembly of wheat contigs were
performed by CAP3 (http://pbil.univ-lyon1.fr/cap3.php).
6.2.4 Synteny between wheat, rice and Brachypodium distachyon
6.2.4.1 Wheat 7BS and rice chromosomes 6 and 8
Information on the synteny of wheat 7BS with rice (Oryza sativa var japonica) physical
and genetic maps was drawn from Wheat Genome Database of JCVI
(http://jcvi.org/wheat/wheat_syn_dload.php) and Gramene database
(www.gramene.com) respectively. Further detailed information on the BAC and PAC
sequences of rice were obtained from Gramene website and their links to NCBI
(www.ncbi.nlm.nih.gov/), and ENA of EMBI-EBI (http://www.ebi.ac.uk/ena).
Information on the genes in these BAC and PAC sequences was viewed with the Rice
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Genome Browser of MSU Rice Genome Annotation (Osa1) Release 6.1
(http://rice.plantbiology.msu.edu/cgi-bin/gbrowse/rice/#search).
6.2.4.2 Wheat and Brachypodium distachyon
Information on synteny between wheat and Brachypodium distachyon was drawn from
www.wheatgenome.info and ModelCrop databases. The information from rice,
Brachypodium and wheat were compiled and ordered based on physical maps in
ModelCrop and Gramene databases.
6.2.5 Multiple alignment and structural analysis of candidate sequences
Multiple alignments were performed with MAFFT engine
(http://www.ebi.ac.uk/Tools/msa/mafft/). The alignments were then transferred to
GeneDoc version 2.7.000 (http://www.nrbsc.org/gfx/genedoc/) for further multiple
alignment editing, shading, structure analysis and development of RasMolscript (.scr)
files. Initial information on the glycosyltransferases was obtained from the databases of
Carbohydrate-Active EnZYmes (www.cazy.org), while information for the protein
domain, family and functional sites of the plant O-glycosyltransferases were
downloaded from Prosite database of ExPASy Swiss Institute of Bioinformatics (SIB)
Bioinformatics Resource Portal (http://prosite.expasy.org/). The PDB files for the UDP-
glucose: flavonoid 3-O-glycosyltransferase from VvGT1 (2CIX) (Offen et al. 2006)
were obtained from RSCB Protein Data Bank
(http://www.rcsb.org/pdb/home/home.do). The correlation between the multiple
alignments and the structural information of the PDB file were obtained from S2C
facility (http://www.fccc.edu/research/labs/dunbrack/s2c). The 3-D molecular structure
of the alignment was then viewed by RasWin molecular Graphic version 2.7.4.2
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(www.rasmol.org). The amino acid sequence conservation and polymorphism was
visualised by weblogo (weblogo.berkerley.edu).
6.3 Results and discussion
6.3.1 ACG content and composition of Sunco/Tasman parents and
doubled haploid population
Sunco and Tasman differed from each other for ACG1 and ACG2 concentration, for the
ACG1/ACG2 ratio and for ACG2 content per grain, with Sunco having higher ACG1
concentration (p<0.05) and ACG1/ACG2 (p<0.001) and Tasman having the higher
ACG2 concentration and content per grain (p<0.05). Although the differences in total
ACG concentration, total ACG content per grain and 100 grain weight between Sunco
and Tasman were not significant (p>0.05), Tasman was slightly higher than Sunco for
these three traits. The ACG1 content in the grain of Sunco was higher than Tasman,
however, again the difference was not significant (p>0.05).
ACG concentration (g/g) and ACG content (g/grain) were normally distributed in the
population (Figure 6.2) consistent with the results presented in chapter IV and the
conclusion that these traits appear to be controlled by multiple genes. By contrast, the
frequency distribution for ACG1/ACG2 ratio was bimodal (Supplemental material 3.5).
This is also consistent with the results in chapter IV and the conclusion that the
observed variation for this trait in the Sunco/Tasman population is regulated by a single
gene.
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Figure 6.1 The ACG traits in the parents of the Sunco/Tasman doubled haploid
population used for fine mapping.
0.0
20.0
40.0
60.0
80.0
Sunco Tasman
Parent lines
ACG1 concentration (g/g)
0.0
30.0
60.0
90.0
120.0
Sunco Tasman
Parent lines
ACG2 concentration (g/g)
0.030.060.090.0
120.0150.0180.0
Sunco Tasman
Parent lines
Total ACG concentration (g/g)
0.0
1.0
2.0
3.0
4.0
Sunco Tasman
Parent lines
ACG1 content (g/grain)
0.0
1.5
3.0
4.5
6.0
Sunco Tasman
Parent lines
ACG2 content (g/grain)
0.0
2.0
4.0
6.0
8.0
Sunco Tasman
Parent lines
Total ACG content (g/grain)
0.00.20.40.60.81.01.2
Sunco Tasman
Parent lines
ACG1/ACG2 Ratio
0.01.02.03.04.05.06.0
Sunco Tasman
Parent lines
100 grain weight (g)
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Figure 6.2 Frequency distributions for ACG traits in the Sunco/Tasman doubled haploid population used for fine mapping. The blue
arrows indicated the means of the trait for the parents (T: Tasman, S: Sunco).
Numbers of lines
ACG1 concentration (g/g)
Numbers of lines
ACG1 content (g/grain)
Numbers of lines
Numbers of lines
ACG2 concentration (g/g)
ACG2 content (g/grain)
Total ACG concentration (g/g)
Numbers of lines
Total ACG content (g/grain)
Numbers of lines
T
S TS S
S
T
S
S
T
TT
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6.3.2 QTL for ACG content and composition in Sunco/Tasman
The genetic maps of the 21 chromosomes of Sunco/Tasman include a total of 361
markers (Supplemental material 6.1).
The most significant QTL detected was at the wmc76 marker locus at the 18.0 cM of
chromosome 7B. At this position, the allele from Tasman had negative effects on ACG1
concentration and content and positive effect on ACG2 concentration and content and
thus a strong negative effect on the ACG1/ACG2 ratio. Smaller effects on some of these
traits were detected at on chromosomes 4A and 4B. At the cdo795 marker locus at the
5.7-cM on chromosome 4A, the Tasman allele had a negative effect on ACG2
concentration. Near the marker loci gwm495 (at 16.4 cM) and gwm113 (at 14.9 cM) on
chromosome 4B, the Tasman allele was associated with larger grain and lower ACG
(ACG1, ACG2 and total) concentration) than the Sunco allele. There were also QTL on
chromosomes 2B and 4D that affected grain size, with no effect on ACG traits.
QTL located on 7BS for ACG1/ACG2 ratio, ACG1 concentration (μg/g) ACG1 content
(μg/grain) and total ACG concentration (μg/g) were associated with a negative additive
effect (Table 6.2); in other words, replacing the Sunco allele with the Tasman allele
resulted in a reduction in trait magnitude. Conversely, ACG2 concentration (μg/grain)
and content per grain were associated with positive additive effects (Table 6.2;
supplemental materials 6.2). No significant epistatic interactions were observed. In view
of the very high percent of variation in ACG traits explained by the QTL on 7BS, this
region clearly warranted further investigation and was selected for fine mapping.
129
Major QTL for 100 grain weight were located on chromosomes 2B (LOD 5.42), 4B
(LOD 9.57), and 4D (LOD 5.68), consistent with an earlier report by Mares and
Campbell (2001). The QTL on 2B was located on a chromosome segment translocated
from Triticum timopheevii (Friebe et al. 1996, Kammholz et al. 2001) that also contains
QTL for flour yield (Lehmensiek et al. 2006) stem rust resistance and black point
resistance (Lehmensiek et al. 2006, Christopher et al. 2007). Within the Sunco/Tasman
population, the presence of the Sunco allele at the grain weight QTL-2B was associated
with an 8 – 12% reduction in mean grain weight compared with the Tasman allele
(Mares unpublished data). Whilst the 2B QTL explained nearly 18% of the variation in
grain weight in the current analysis (Table 6.2), it appeared to have little impact, apart
from a suggestive effect on total ACG content (μg/grain), on ACG concentration or
content (Supplemental material 6.2). By contrast, the 4B QTL that explained nearly
27% of the variation in grain weight had a significant impact on ACG1, ACG2 and total
ACG concentration. The 4D QTL by comparison had a significantly weaker effect on
grain weight and no effect on the ACG traits.
The marker nearest the peak of the minor QTL on 4B (ACG1 concentration, ACG2
concentration, total ACG concentration, and total ACG content), gwm495, was located
close to csME1, a perfect marker derived from the semi-dwarfing gene, Rht1. Similarly,
the closest marker to the 100 grain weight locus on 4D, csME2, is derived from the
other common semi-dwarfing gene, Rht2. These genes have been reported to have a
pleiotrophic effect on grain size (Pinthus and Gale, 1990; Rebetzke and Richards,
2000). Mares & Campbell (2001) reported an association of a 4B QTL with flour and
noodle colour (b*) that could not be related to xanthophyll content and suggested that
this was possibly an indirect effect of grain size on milling and flour quality. An SSR
130
marker, wmc48, located 3cM on the telomeric side of gwm495, was reported to be
influence flour yield and kernel hardness (Lehmensiek et al. 2006).
Sunco contains the semi-dwarfing gene, Rht1, on 4B whilst Tasman has Rht2 on 4D
(Ellis et al. 2002 in Lehmensiek et al. 2006). As a consequence the Sunco/Tasman
doubled haploid population consists of lines with tall (rht1, rht2) with genotypes BA
(Tasman B and Sunco A), semi-dwarf (Rht1, rht2 or rht1, Rht2) with genotypes AA and
BB respectively and extreme dwarf (Rht1, Rht2) phenotype with genotypes AB. Mares
and Campbell (2001) reported significant differences in the means of grain size between
these phenotype classes. Moreover, as the means of the plant height in 1998 decreased
in 1999, the means of the 1000-kernel weight also decreased; from 42.4 to 44.35 for the
tall group, from 36.9 to 40.73 for the semi-dwarf and from 30.1 to 33.7 for the dwarf
groups.
The 4A QTL for ACG2 concentration explained only 4% of the variation, could not be
associated with any previously reported genetic effects on grain size or grain
constituents and was not pursued further in this study.
131
Table 6.2 QTL associated with ACG traits in Sunco/Tasman doubled haploid population. The QTL were backward selected from the
genome scan with CIM. All of these QTL are significant at LOD threshold = 3.405, except *.
%Explain variation
Additive effect
Standard Error
2B wmc35a 50.6 100 grain weight (g) 9.905 17.762 0.262 0.0384A cdo795 5.7 ACG2 concentration (g/g) 3.793 4.412 -5.733 1.481
ACG1 concentration (g/g) 3.376 5.119 -5.162 1.431ACG2 concentration (g/g) 3.866 4.524 -5.805 1.482Total ACG concentration (g/g) 3.761 8.93 -10.553 2.741
gwm113 14.9 100 grain weight (g) 14.196 26.966 0.323 0.0374D csME2 0 100 grain weight (g) 5.851 8.928 -0.186 0.037
ACG1 concentration (g/g) 15.83 35.408 -13.575 1.458ACG1 content (g/grain) 10.715 26.813 -0.499 0.069ACG2 concentration (g/g) 24.761 49.517 19.204 1.513ACG2 content (g/grain) 20.469 46.411 0.823 0.074ACG1/ACG2 ratio 58.893 85.894 -0.241 0.009
wmc767B
4B 16.4
18
gwm495
Closest markers Estimated QTL peak positionChromosomes
QTL effectsTraits LOD
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6.3.3 Fine mapping of ACG QTL on 7BS of Sunco/Tasman
6.3.3.1 Additional markers
Of the 67 SSR markers that were tested for polymorphism in the Sunco/Tasman
doubled haploid population, 27 were polymorphic. However, only 11 were added to the
map due to missing genotype data or distortion of the frequency of the marker genotype
towards one of the parents (Supplemental material 6.3). Five markers from the long arm
of the original map were excluded because the distance between two closest markers
from the short arm and the long arm exceeded 90 cM.
Two of the 6 SNP markers, BE352570 and BE445287, shown by Dr. Matt Hayden
(pers.comm) to be polymorphic between Sunco and Tasman were successfully mapped.
Sequencing of the other ESTs: BE518436, BF201699, BQ169669, and BQ171683 to
obtain reference sequences for designing the primers to amplify the SNP were
unsuccessful. The BE352570 contig was successfully sequenced and an allele apecific
primer (ASP) was designed (Figure 6.3A). The genome specific primers (GSP) for this
EST sequence were used as locus specific primers (LSP) to amplify the EST. The
amplified sequences were then re-run with the Allele Specific Primers (ASP). This
marker was successfully assayed (Figure 6.3B) in 271 lines of the doubled haploid
populations. Two SNP markers were designed from the BE445287 contig (Figure
6.4A). However, only one of the BE445287 SNP markers was successfully assayed in
129 lines (Figure 6.4B) and included in the map. The other marker was polymorphic
between Sunco and Tasman and in the panel of 20 doubled haploid lines but could not
be scored on the majority of the doubled haploid lines (Figure 6.5C).
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Figure 6.3 Positions of the ASP and GSP primers for the SNP marker derived from the
BE352570 EST contig, I. The design of specific primer (LSP) (genome specific primers
that were re-used to amplify the specific EST locus), and allele specific primer (ALS).
B. The polymorphisms of the SNP marker within BE352570 EST (573bp); II. typical
banding patterns obtained with some of the doubled haploid lines (#DH80 to #DH92).
Bands scored as: A for Sunco alleles and B for Tasman alleles.
BE352570 Contig P1SB
7 50 bp
SNP Sunco/Tasman A/G
GSP:oGW001F GSP:oGW001R
LSP:oGW0012F LSP:oGW0012R
ASP:oGW0013R
BE352570 contig
750bp
I
II
134
Figure 6.4 SNP markers designed from BE445287 EST contig. I. The design of specific
primer (LSP) (genome specific primers were re-used), and 2 allele specific primers
(ALS). II. The polymorphisms of the first BE445287 SNP markers in some of the
doubled haploid lines (#DH54 to 68), III. The polymorphisms of the second BE445287
SNP markers in some of the doubled haploid lines (#DH31 to 43). Both markers were
scored as A and B alleles: A for Sunco alleles and B for Tasman alleles.
BE455287 Contig P2SB
7 30 bp
SNP Sunco/Tasman A/G
SNP Sunco/Tasman G/C
LSP: oGW0021F LSP: oGW0021R
ASP: oGW0022F
ASP: oGW0023F
GSP:oGW002RGSP:oGW002F
BE455287 Contig P2SB730 bp
II
III
I
135
6.3.3.2 The order of SSR markers within the QTL on 7BS of
Sunco/Tasman compared with other populations and a consensus map
Seven additional markers were mapped into the interval, gwm400 to wmc76, containing
the major QTL on chromosome 7BS while 6 other markers were mapped on the
centromeric side of this region (Fig. 6.5). These additional markers reduced the
confidence interval of the QTL peak from 28.8cM between gwm400 and sun16 to
5.5cM, flanked by wmc426 and sun16.
Prior to fine mapping, the order of the markers on Sunco/Tasman 7BS was similar to
that in the maps of Synthetic/Opata (BARC) and Chinese Spring/SQ1 (Figure 6.5).
However, this order was not consistent with that in the consensus map, where the
wmc76 was located proximal to gwm400. After 13 more markers were mapped into the
region, the order of the markers on 7BS of Sunco/Tasman was still similar to Chinese
Spring/SQ1, both for the original markers and the additional markers, to the original 7B
markers in the Synthetic/Opata map and to the additional markers in the wheat
consensus map. However, the order of the additional markers was no longer consistent
with that in the Synthetic/Opata (BARC) map.
6.3.3.3 QTL for the ACG traits
Major QTL that affected 5 traits of ACG content, concentration and ratio were
confirmed on 7BS between wmc426 and sun16 (an interval of 5.5cM distant) (Table 6.3
and supplemental material 6.4). The peak of the major QTL for ACG2 concentration
and ACG1/ACG2 ratio were still very close to wmc76, and explained 15.5% and 48.6%
of the variation in these traits respectively. About 0.8 cM distal to this ratio QTL, a
major QTL peak for ACG2 content (g/grain) was detected very close to wmc426 that
136
explained 12.9% of the variation. The QTL for both ACG1 concentration and content
were detected 4.7cM proximal to wmc76, very close to sun16 explaining 13.8% and
13.6% of variation respectively.
137
Figure 6.5 Order of markers on 7BS of Sunco/Tasman doubled haploid population
before and after fine mapping compared with the order in other genetic maps
(Synthetic/Opata (BARC), Chinese Spring/SQ1 and a Consensus map (Somers et al.
2004) sourced from Graingenes databases (access 10 October 2011). Markers and
arrows in red are the order of the markers before the fine mapping, while those in blue
are the ordered for the additional markers added in this study. Markers in black are
other markers in each chromosome that are not in 7BS fine map. Numbering to the left
of the chromosomes represents genetic distance (cM).
138
The ACG1/ACG2 ratio in the Sunco/Tasman doubled haploid population gave a
bimodal frequency distribution and was also mapped as a binary trait (A-high ratio/B-
low ratio) (Figure 6.6 and Table 6.4). The QTL peak was located between wmc76 and
sun16, an interval of 4.7cM, and explained 55.3% of the variation. The difference
between explained variation before addition of markers in the QTL region and after was
noted. This might be due to the increase in the numbers of phenotypic data values that
are in the transitional range between 0.7-0.8 in the data set with 275 doubled haploid
lines. There are 27 of them in this data set, while in the 153 doubled haploid lines there
was only 1.
139
Table 6.3 QTL on 7BS of Sunco/Tasman after additional SSR markers were added.
Table 6.4 QTL and QTL effect for ACG1/ACG2 ratio analysed as a binary trait A/B (Data output from GENSTAT 14 QTL Analysis,
Single Trait Linkage Analysis (Single Environment).
%Variation explained Additive effect Standard
Error7B sun16 30.4 ACG1 concentration (g/g) 9.4 13.8 -6.6 1.0
wmc0076 25.7 ACG2 concentration (g/g) 10.9 15.5 8.9 1.3 sun16 30.4 ACG1 content (g/grain) 9.3 13.6 -0.3 0.0
wmc0426 24.9 ACG2 content (g/grain) 9.1 12.9 0.4 0.1 wmc0076 25.7 ACG1/ACG2 Ratio 40.9 48.8 -0.2 0.0
TraitsQTL effects
Chromosome Nearest markersEstimated QTL peak
position (cM)LOD
QTLNearest Markers wmc76Estimated peak position 25.7Interval 12.8-38.6LOD 49.1
QTL effect% variation explained 55.3Additive effect -0.4Standard error 0.02
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Figure 6.6 QTL on 7BS for ACG1/ACG2 ratio analysed as a binary trait A/B (A: high
ratio, B: low ratio). Red line = LOD threshold at Fpr<0.001.
0 10 20 30 40 50 60 70LOD
141
6.3.4 Synteny between the wheat 7BS chromosome region harbouring the
QTL associated with variation in ACG traits with the physical maps of
rice and Brachypodium distachyon
6.3.4.1 Synteny with rice chromosomes 6 and 8
The 7BS QTL region was aligned to chromosome 6 of rice using EST sequence
BE352570 containing a SNP marker. This marker was located 3.1 cM distal to the QTL
peak on 7BS of wheat and the EST was mapped to the short arm of chromosome 6 of
rice at the position of (AP005387 PAC/BAC clone) (Fig.6.7). The BE352570 EST
sequence of bread wheat had 88% identity with LOC_Os06g15990, annotated as
ALDH2B, an expressed gene sequence for aldehyde dehydrogenase SALDEHYD-RXN
1:2.1-AST-PWY arginine degradation II, for 82 nucleotides.
This region where AP005387 mapped, also aligned with 2 tightly linked QTL for brown
plant hopper resistance (Bph3 and Bph4) on chromosome arm 6S in IR64/Azucena, rice
doubled haploid population (Cornell DH QTL 2001, Gramene database). The ACG1
from rice phloem has been reported to be a feeding inhibitor and resistance factor for
brown plant hopper, Nirlaparvata lugens (Stevenson et al. 1996). A bi-functional UDP-
glucuronyltransferase and UDP-glucosyltransferase was located 9.727kbp to the
centromeric side of LOC_Os06g15990. A region that is rich in expressed putative
glycosyltransferase genes was also located 6 PAC/BAC clones to the centromeric side
of AP005387. There are 11 putative glycosyltransferases (expressed) genes spread
across 8 PAC/BAC clones (AP005695 to AP005761) in this region and a basic/helix-
loop-helix (bHLH) 86 like protein coded by LOC_Os06g16400 at AP003044, 3 BAC
142
clones from the syntenic locus. The complete list of expressed proteins and putative
proteins in this region is contained in supplemental material 6.5.
The chromosome region immediately to the centromeric side of the 7BS QTL was
aligned to rice chromosome arm 8L using BE445287 SNP marker (Fig. 6.8). The
BE445287 EST sequence was located 3.6cM to the centromeric side of the 7BS QTL
region and aligned with LOC_Os08g40530 at AP004761 PAC/BAC clone of rice 8L
(93.8% identity).
LOC_Os08g40530 on rice 8L expressed a putative calcium-transporting ATPase 9,
plasma membrane-type protein. Other putative genes of interest in rice PAC/BAC
clones close to the SNP marker, included dihydroflavonol 4-reductase (DFR)
(LOC_Os08g40440, AP004761), 5 cytochrome-P450 monooxygenase genes spread
across 3 PAC/BAC clones (AP005816 to AP005254), and a sequence containing a
basic/helix-loop-helix (bHLH) 91 DNA binding domain. The putative protein sequences
expressed by the genes located in these clones are listed in supplemental material
6.6.The interaction between myb and bHLH transcription factors was reported to result
in the activation of branches of the flavonoid pathway that compete for precursor
required for the ACG biosynthesis and which which lead to anthocyanin,
proanthocyanin and flavonol glycoside biosynthesis (Bogs et al. 2007, Goff et al. 1992,
Nakatsuka et al. 2008). These transcription factors were reported to up-regulate DFR
genes involved in producing red seed coat colour (Himi et al., 2005).
When recombinants were arranged in order from the distal end of the chromosome
towards the centromere (as described for boron tolerance in Schnurbusch et al. 2006), a
change from Sunco allele to Tasman allele between wmc76 and sun16 was associated
143
with a change in ratio from Sunco type to Tasman type. These markers appear to be
much closer to the SNP linking 7BS with rice chromosome 6S than the SNP linking
7BS with rice chromosome 8L. As a consequence, the synteny with rice chromosome
6S would seem to be more relevant to control of variation in ratio and the
glycosyltransferase(s) more likely as the candidate gene for ACG1/ACG2 ratio than the
transcription factors.
The region containing the minor QTL on 4B for ACG content in Sunco/Tasman was
syntenic with rice chromosome 3 (supplemental material 6.7). The synteny analysis was
performed in silico by aligning the Sunco/Tasman QTL region with the wheat physical
map, SSR (Grain genes 2003), then aligning this second map with the wheat physical
map, EST (Grain genes 2003). ESTs that were located in the predicted deletion bin
containing the QTL were used to align the deletion bin with rice chromosome 3.
Although the region around the 4B QTL of Sunco/Tasman is quite dense with markers,
with 5 markers within 4.5cM; the syntenic region in rice chromosome still covered a
large section (15-27Mbp). In addition, given that this QTL appears likely to be co-
located with the semi-dwarfing gene, Rht1, it is probably worthwhile to examine this
region in other bread wheat populations, where parents show greater variation for total
ACG concentration and grain content.
The wheat-rice synteny seemed not to be as direct and continuous as previously
explained by (Sorrells et al. 2003). Disruptions by homology of small numbers of genes
with other chromosomes, genomic sequences from other chromosomes were observed,
e.g. wheat 7B - rice 6 is interrupted by a section of rice chromosome 5, and there are
genes/wheat sequences on wheat 3B that are syntenic with rice chromosome 6. Four
144
wheat EST sequences at 3B are similar to 8 sequences on rice 6S while 3 others are
similar to 7 sequences on 6L (Supplemental material 6.8). Wheat EST BF485490
(729,556,473bp at 3BL) is syntenic with a block of sequences between AP004725
(7,634,956kb) and AP004651 (7,636,291kb), from LOC_Os06g13640 to
LOC_Os06g13910. Two glycosyltransferases were located at LOC_Os06g13710 and
LOC_Os06g13760. The complete list of these sequences is presented in Supplemental
material 6.8. The occurrence of these disruptions have also been reported by (Francki et
al. 2004).
145
Figure 6.7 Comparative map of 7BS Sunco/Tasman, rice physical map 6S and rice RI64/Azucena 6S. The markers and loci in red are markers that link 7BS and rice 6S of physical map and markers that flank the QTL region in rice. Locus in grey box: F2H, loci in red boxes: glycosyltransferases. Blue bar QACG-7B: QTL for ACG trait at 7B, red bar Bph: QTL for brown plant hopper resistance. Numbers on the left of Sunco/Tasman 7BS and rice IR64/Azucena maps show the genetic distance between markers (cM), while those on the left of rice physical map 6S show the distancein kilo base pairs (kb). On the Sunco/Tasman map, 3.1cM is the distance between SNP marker BE352570 and wmc76, nearest marker to ratio QTL, while 5.5 cM is the size of the chromosome intervalL between wmc426 and sun16. Information on the rice physical map 6S and rice RI64/Azucena 6S genetic map was obtained from the Gramene database.
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Figure 6.8 Comparison of Sunco/Tasman 7BS with the physical map of rice 8L (Gramene database). The 7BS marker in red is the wheat
EST SNP marker used to link the two maps. The blue bar marked QACG-7B is the QTL region on 7BS for ACG traits (Table 6.3).
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6.3.4.2 Synteny with Brachypodium distachyon chromosomes 1 and 3
The 7BS chromosome arm of wheat is syntenic with chromosomes 1 and 3 of
Brachypodium distachyon. The SNP marker from EST BE352570 linked 7BS of
Sunco/Tasman with chromosome 1 of Brachypodium distachyon (Figure 6.9) at
BRADI1G43770 locus (41.5Mbp), while that from EST BE455287 linked 7BS with
chromosome 3 (Figure 6.10) at BRADI3G40640 (42.7Mb). A block of loci in rice
chromosome 6S (2.6Mbp-13Mbp) was syntenic with Brachypodium distachyon
chromosome 1 (Os6_Bd1_R.1: 39.8Mbp-48.1Mbp) (supplemental material 6.9 and
6.10), while, a block of loci on rice chromosome 8L (19.4Mbp-28.1Mbp) was syntenic
with Brachypodium distachyon chromosome 3 (Os08_Bd3_F.1: 37.8Mbp-44.4Mbp)
(supplemental material 6.11).
The relationship between wheat 7BS genetic map and Brachypodium distachyon
physical map chromosome 3 was established through the synteny between Aegilops
tauschii reference map (Dvorak et al. 1995) and Brachypodium distachyon comparative
map. Berkman et al. (2012) established a syntenic build between wheat homoeologous
group 7 and Brachypodium distachyon chromosome 1. Approximately 13% of the genes
on 7BS have been translocated to 4AL, and this translocation region that was marked by
BRADIg49510 to the telomere showed a similar gene content to 7BS and 7DS
(Berkman et al. 2012). 7DS and 7BS sequences distal to this translocation region were
highly conserved. No information is available yet for the syntenic build between group
7 and chromosome 3. The SNP marker BE455287 at 7BS Sunco/Tasman was not
available in Brachypodium distachyon chromosome 3, and does not have corresponding
EST cluster in the comparative map. However, such information was available for 7DS.
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The glycosyltranferase sequences homologous to those on rice chromosome 6S are
located on chromosome 1 of Brachypodium distachyon, but were ordered in the
opposite direction to rice. Four rice glycosyltranferases, LOC_Os06g17250,
LOC_Os06g17220, LOC_Os06g17140 and LOC_Os06g17120, were aligned to
BRADI1G43600 (41.4Mbp), while 3 others, LOC_Os06g18670, LOC_Os06g18790, and
LOC_Os06g17020, were aligned to BRADI1G44630 (42.7Mbp). No loci harboring
sequences homologous to LOC_Os06g17260 or LOC_Os06g18140.0 were found. Only
4 out of 11 glycosyltransferases in the region of rice syntenic to 7BS were identified in
Brachypodium distachyon chromosome 1.
Epimerases, galactosyltranferases and DFR gene sequences identified in chromosome
8L of rice were also in Brachypodium distachyon chromosome 3. The order of loci are
very similar, but rice chromosome has more loci that has been annotated and syntenic
with wheat than the Brachypodium distachyon chromosome.
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Figure 6.9 Comparison of the Sunco/Tasman 7BS genetic map, with the Brachypodium distachyon physical map of chromosome 1 and the rice physical map of 6S (Gramene database). Loci in red indicate the linkage between maps. The arrows show the order of the loci. The physical maps are based on information from Gramene database. Blue bar QACG-7B: QTL for ACG traits at 7BS. Numbers on the left of Sunco/Tasman 7BS show the genetic distance between markers (cM), while those on the right of Brachypodium distcahyon and rice physical maps show distance in kilo base pairs (kb).
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Figure 6.10 Comparison of the maps for Sunco/Tasman genetic map 7BS, Aegilops tauschii 7D (Reference map of Dvorak (2009), Brachypodium distachyon chromosome 3 (Comparative map 0.1, and physical map (Gramene Release 31) were obtained from Gramene database). Blue bar QACG-7B: QTL for ACG trait at 7BS. Marker in red (BE445287) at 7BS Sunco/Tasman link this population map to A. tauschii reference map, which structural relationship with the Brachypodium distachyon comparative map has been established. Red lines showed the links, while markers in yellow boxes are the markers that link the A. tauchii reference map and the Brachypodium distachyon map. The purple lines show the relationship between the wheat EST in the wheat map and annotated EST cluster in the Brachypodium map.
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6.3.5 Candidate genes related to variation in ACG biosynthesis in wheat
Based on the biosynthetic pathway, there are several types of genes that might be
candidates for regulating the ACG biosynthesis. These genes include those early in the
common pathway to ACG1 and ACG2. Firstly, the transcription factors that have been
reported for flavonoid biosynthesis. They generally activate large sections of the
pathway not individual steps. Secondly, the genes that function later in the pathway.
They are more likely to determine the ratio and content of ACG1 and ACG2. This
particular part of the pathway involves the transfer of glucose and galactose molecules
to the open hemiketal ring structure. In addition, both ACGs contain arabinose, and
hence epimerases and sugar transporters may be important in controlling the relative
concentrations of UDP sugars.
6.3.5.1 The glycosyltransferases
The phylogenetic tree of these putative glycosyltransferases is presented in Figure 6.11.
These 11 sequences were grouped into 2 main clades. The first clade (in the blue box)
was closer to the previously reported plant O-glycosyltransferases: UDP-glucosyl and
glucuronosyl transferase of maize bronze alleles Bz-W22 (Furtek et al. 1988, Ralston et
al. 1988), UDP-glucose:flavonoid 3-O-glycosyltransferase with ability to transfer UDP
galactose in Vitis vitifera VvGT1 (Offen et al. 2006), UDP-glucuronic acid:flavonol-3-
O-glucuronosyltransferase (GAT) of Vitis Vitifera VvGT5 (Ono et al. 2010), and UDP-
glucose/UDP-galactose:flavonol-3-O-glucosyltransferase/galactosyltransferase of Vitis
Vitifera VvGT6 (Ono et al. 2010). The C-glycosyltransferase of rice (OsCGT) that was
previously reported by Brazier-Hicks et al. (2009) together with its orthologue in
Brachypodium distachyon (BRADI1G43410) and Sorghum bicolor were also in this
group.
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The second group of 5 putative UDP-glucose glycosyltransferases (in the red box) has
similar amino acid sequences to the O-glucosyltranferases reported at V25L and W168S
of the N-terminal domain, that are polymorphic with the first group containing C-
glycosyltransferase and its 2 orthologues (Supplemental material 6.10). The amino acid
signature of the plant secondary product glycosyltransferase motif (PSPG) of these 11
sequences is conserved, except for the Gln-44 (Q) (Figure 6.12). Polymorphism was
observed in the first clade that contained the rice C-glycosyltransferase and its ortholog.
Two sequences, LOC_Os06g18670 and LOC_Os06g18790 have histidine instead of
glycine. The last two amino acids of the PSPG motif Glu43 (D) and Gln44 (Q) interact
with glucose moiety of the sugar donor, through formation of hydrogen bonds with its
2-, 3-, and 4-OH (Osmani et al. 2009, Wang 2009). The mutation of H374Q switched
sugar donor preference from UDP-galactose to UDP-glucose (Kubo et al. 2004). But,
this does not appear to work the other way around, since the change abolished activity
with both of the sugars (Offen et al. 2006).
The N-terminal domain is less conserved than the C-terminal domain and is involved in
determining sugar donor specificity (Osmani et al. 2009). The polymorphisms between
the C-glycosyltransferase-like sequence group and the putative O-glycosyltransferase
were located at the beginning of the sequence N1 (before the loop N1) and at loopN4
(Figure 6.13). These loops have been reported to be crucial for the sugar acceptor
pocket formation (Brazier-Hicks et al. 2007, Li et al. 2007, Offen et al. 2006, Osmani et
al. 2009, Shao et al. 2005, Wang 2009).
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Figure 6.11 Phylogenetic tree of the putative UDP-glycosyltransferases in the region of rice chromosome 6 that is syntenic with the ratio QTL on
Sunco/Tasman compared with other UDP-glycosyltransferases: Bz1-W22 (Maize UDPG-flavonoid 3-O-glucosyltransferase), BRADI1G43410.1 and
Sb10g010640.1 (Brachypodium distacyon and Sorghum bicolour glycosyltransferases that were the orthologs of rice C-glycosyltransferase (OSCGT,
LOC_Os06g18010.1), UGT71G1(Medicago truncatula flavonoid/triterpene O-glucosyltransferase, VvGT5 (Vitis vitifera UDP-glucuronic
acid:flavonol-3-O-glucuronyltransferase), VvGT6 (Vitis vitifera bifunctional UDP-glucose/UDP-galactose: flavonol-3-O-
glucosyl/galactosyltransferase) and VvGT1 (Vitis vitifera UDP-glucose:flavonoid 3-O-glycosyltransferase). The cereal protein sequences were obtained
from Gamene website, while the other protein sequences were obtained from NCBI databases. Blue box: first clade, red box: second clade.
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Figure 6.12 Conserved region of the Plant Secondary Product Glycosyltransferase (PSPG)
motif of the putative UDP-glycosyltransferases from the region of rice chromosome 6 that is
syntenic with the ratio QTL on 7BS of Sunco/Tasman. N and C at the x axis of the weblogo
showed the direction from N-terminal to C-terminal of the protein sequence; the height of the
letter stacks showed the conservation of the amino acid, and the height of the letters within the
stack indicates the relative frequency of each amino acid at that position. The arrow shows the
amino acid polymorphism for UDP-glucose recognition and UDP-galactose recognition (D).
The D463H mutation converted the bifunctional UDP-glycosyltransferase to a monofunctional
galactosyltransferase (Kubo et al. 2004, Offen et al. 2006, Ono et al. 2010, Osmani et al. 2009).
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Figure 6.13 Model of VvGT1 and position of the amino acid highlighted in supplemental material 6.12. The red-maroon ribbons show the -helix structure position, while the white ribbon shows the -helix and loop structure position. The dark blue ribbon shows the position of the PSPG motif. Small segments of the ribbon in red, purple and gold colour show the positions of the amino acid polymorphism, while those in light blue, green and yellow show the position of the conserved amino acids. The ball and stick structure in the middle of the stereo molecule are the flavonoid and UDP-glucose substrate molecules. The VvGT1 backbone was re-drawn from the PDB file for the UDP-glucose: flavonoid 3-O-glycosyltransferase of VvGT1 (2CIX) (Offen et.al. 2001) and this file was obtained from RSCB Protein Data Bank (http://www.rcsb.org/pdb/home/home.do). The 3D secondary structure was re-drawn from Osmani et al. (2009), while the conservation and polymorphism of amino acids were drawn from Shao et al. (2005). Information for the protein domain, family and functional sites of the plant O-glycosyltransferases were downloaded from Prosite database of ExPASy Swiss Institute of Bioinformatics (SIB) Bioinformatics Resource Portal (http://prosite.expasy.org/), while the correlation between the multiple alignments and the structural information of the PDB file were obtained from the S2C facility (http://www.fccc.edu/research/labs/dunbrack/s2c). Further details are explained in the text.
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6.3.5.2 Other candidate genes for the major and minor QTL associated
with ACG content and composition.
A putative F2H gene, LOC_Os06g01250, is located at the distal end of chromosome 6S
(start at 162,205bp). This gene is a candidate for the first part of the proposed
biosynthetic pathway for ACG (Figure 2.5) where naringenin flavanone is converted to
2-hydroxy flavanone. F2H activity may be involved in the control of the total
concentration and total content of ACG.
Other candidate genes possibly related to the availablity of the UDP-sugars required by
the glycosyltransferases are genes coding for epimerases or UDP-sugar transporters.
Genes coding for two putative expressed NAD dependent epimerase/dehydratase family
proteins (Q8H0B2) with putative UDP-arabinose/glucose 4-epimerase 3 activity (that
catalyses the conversion of UDP-galactose to UDP-glucose), LOC_Os08g03570 and
LOC_Os08g28730, were located in PAC/BAC AP004591 and AP004397 respectively
(Figure 6.8). The LOC_Os08g03570 locus is a homolog of BE498418 wheat EST at C-
7BL2-0.33 in the C-7AL1-0.39 deletion bin of Chinese Spring. The homologies are
observed at exons 5, 6, and 7 with 87%, 91% and 93% sequence identity for 89, 140,
and 148 nucleotides. The wheat and rice exons are generally conserved, while the
introns have less similarity, as previously reported in cereals (Bossolini et al. 2007, Li
et al. 1999)
A wheat EST, annotated as a glucose-6-phosphate transporter (BE443396, Q7XY15),
located in the deletion bin C-7BS1-0.27 that contains the major ACG QTL at 7BS of
Sunco/Tasman, is a homolog of LOC_Os08g08840 (AP004656), located on
chromosome 8 of rice (start at 5,138,640bp) (Figure 6.8). There are two exons in this
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genomic sequence. One exon had 89.63% identity (for 241 nucleotides of the 3rd exon)
and the other was at 91% identity (for 59 nucleotides of the 2nd exon) with the wheat
EST.
A wheat EST annotated as a galactose transporter, BE498418, located within the C-
7BL2-0.33 deletion bin of Chinese Spring is a homolog with 89 % identity (for 113
nucleotides) of exon 7 of LOC_Os05g02490 of rice chromosome 5. In addition, two
putative expressed galactosyltransferase family proteins were located on chromosome 8
of rice, LOC_Os08g02370 (AP004562) and LOC_Os08g29710 (AP004689). There are
no other glycosyltransferases located in chromosome 8 of rice.
6.4 Conclusion
The 7BS QTL was saturated with SSR markers to reduce the size of the interval and
was shown to be syntenic with a region on chromosome 6 of rice. Eleven putative
glycosyltransferases, an F2H, 2 bhLH transcription factors, 2 epimerases, and sugar
transporters located in this region on rice chromosome 6 were identified as potential
candidate genes controlling the variation in ACG biosynthesis in bread wheat grain.
There are 2 clades of glycosyltransferases on rice 6S region that differ in a single amino
acid at the sugar recognition site. The O‟ and C‟ glycosytranferases differ at V25L and
W168S, very close to, or involved in, the sugar donor pocket. The C-glycosyltransferase
is a possible candidate for the gene controlling the ratio trait based on the combined
information from the nullisomic-tetrasomic Chinese Spring analysis, 7BQTL, synteny
analysis and C-glycosyltransferases sequence and 3-D structure analysis. This
hypothesis could be validated by cloning the homologous wheat 7B C-
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glycosyltransferase, identifying SNP or other markers between Sunco and Tasman
followed by mapping the polymorphisms in the Sunco/Tasman. Moreover, it should
also be possible to follow the expression of the gene in developing grain of Sunco and
Tasman and to determine its temporal relationship to the synthesis of ACG.
Assuming that the candidate gene within the 7BS QTL is a glycosyltranferase then there
are at least 2 models that could explain the observed variation in ACG composition. The
first model is based on the Chinese Spring nullisomic-tetrasomic data presented in
Chapter IV where the absence of chromosome 7B was associated with an increase in
ACG1/ACG2 ratio similar to that found in Sunco and related cultivars. If the
glycosyltransferase located on 7BS has a higher specificity for UDP-galactose than
UDP-glucose; then in its absence, the flow of intermediates might be directed towards
synthesis of the glucose containing ACG, ACG1, assuming that glycosyltransferase(s)
located elsewhere in the genome have a higher specificity for UDP-glucose. In this first
model, Tasman would have the wild-type allele coding for a glycosyltransferase with
higher specificity for UDP-galactose whilst Sunco would have either a null allele or a
mutation that significantly reduced the activity of the encoded glycosyltransferase. The
second model would involve Tasman having a wild-type allele coding for a UDP-
galactose specific glycosyltransferase whilst a mutation in the Sunco allele would be
associated with a switch in specificity from UDP-galactose to UDP-glucose.
By analogy, the very low ACG1/ACG2 ratio observed in the Chinese Spring nulli-7D
lines (Chapter IV) would suggest that there was a gene coding a UDP-glucose specific
glycosyltransferase located on 7DS.
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Major QTL were detected on 7BS for a number of ACG traits whilst minor QTL were
detected at 4B and 4A. The QTL at 4B appeared to coincide with a QTL for grain size
for which the most likely candidate gene is Rht1.Whilst it is possible that there is a
specific gene within this QTL that directly affects ACG synthesis, it appears more likely
that the observed effect on ACG concentration is a pleiotrophic effect of the semi-
dwarfing gene.
The results have a number of implications for variety improvement for YAN and further
research. The QTL for total ACG content could be validated in other populations and
the closely linked markers used in marker-assisted selection. Unfortunately, as shown in
Chapter V, simply increasing total grain ACG does not result in higher flour ACG. A
longer term solution would perhaps be to transform a bread wheat cultivar, preferably
one which already has excellent quality for YAN, with a combination of F2H and
glycosyltransferase genes attached to an endosperm specific promoter in an attempt to
get ACG synthesis in the starchy endosperm. Further research effort could be focused
on cloning the candidate glycosyltransferase gene, validating its role in ACG synthesis
and confirming the UDP-sugar specificity. An additional area for research would be the
mechanism involved in the apparent link between grain size and ACG concentration
and content; and the effect of the plant external factors such as environmental
conditions to this link.
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Chapter VII: Identification of SNPs and haplotypes in
candidate genes for Apigenin di-C-glycoside (ACG)
biosynthesis in bread wheat (Triticum aestivum L.) grain: C-
glycosyltransferase (CGT) and flavanone 2-hydroxylase (F2H)
7.1 Introduction
In the previous chapter, several possible candidate genes for the control of ACG
biosynthesis in bread wheat grain were identified, C-glycosyltransferase (CGT) and
flavanone 2-hydroxylase (F2H). Various PCR based methods have been used to isolate,
purify and clone either F2H or CGT genes. Hicks et al. (2010) successfully cloned CGT
genes from rice genomic DNA (gDNA). In other studies by Ono et al. (2010) and
Noguchi et al. (2009) with the dicotyledonous plants (Vitis vitifera and Lamiales
respectively), flavonoid glycosyltransferase genes from the dicotyledones were cloned
from the complimentary mRNA via cDNA. Du et al. in 2009 and 2010 isolated F2H
from cDNA of rice and sorghum. Neither F2H nor CGT have been cloned from bread
wheat.
However, other flavonoid pathway genes have been cloned in hexaploid bread wheat
and these include F3H (Khleskina et al. 2008), DFR (Himi et al. 2004) and R (myb
transcription factor) (Himi et al. 2005). In all of these studies, multiple copies of the
genes were obtained by PCR amplification. Four copies of F3H were obtained from
cDNA of nullisomic-tetrasomic (NT) lines Chinese Spring: 1 copy from 7A
chromosome, 2 copies from 7B and 1 copy from 7D (Khleskina et al. 2008).
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Meanwhile, Himi et al in 2004 and 2005 recovered three homeoforms of DFR and R
(myb transcription factor) genes from gDNA of NT lines Chinese Spring group 3, one
from each of 3A, 3B, and 3D NT lines.
Having identified potential candidate genes controlling variation in ACG composition
in wheat, the next step is validation. One strategy for achieving this is to isolate and
sequence the genes, then to look for sequence differences between the parents of the
mapping population. Any sequence differences can be used to develop markers that can
be mapped on the population and marker-trait linkage tested. This chapter describes
attempts to amplify CGT and F2H sequences from genomic DNA and cDNA of bread
wheat. Degerate primers were designed based on protein sequence alignment rather than
specific DNA primers for the EST, especially with the CGT, because of the disimilarity
among their DNA sequences. It is expected that similar protein with identity greater
than 35% will have similar functions especially when the functional domains are
homolgous. Unfortunately due to time constraints and difficulties in working with a
very large gene family in hexaploid wheat, this was not successfully completed and
only a progress report is presented here.
7.2 Materials and Methods
7.2.1 Plant Materials
7.2.1.1 gDNA
The wheat genomic DNA template used in this experiment were extracted from the
nullisomic-tetrasomic lines of Chinese Spring group 7, Sunco and Tasman parents,
Sunco and Tasman panel lines; as explained in details in Chapter III section 3.2.3.3. The
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rice genomic DNA used as positive control in this experiment was kindly provided by
Rice Salt Group (ACPFG).
7.2.1.2 mRNA
To obtain wheat RNA, the nullisomic-tetrasomic lines of Chinese Spring group 7,
Sunco, Tasman, Gamut and Kennedy were grown in the glasshouse during August-
December 2010. The heads were harvested during their development, at 10, 15, 20, and
25 days post anthesis. The grains were immediately separated from the head after
harvest, and the embryo were dissected from these grains. Then, both embryos and de-
embryonated grains were put in aluminium foil, and frozen immediately in liquid
nitrogen. The dissected samples were then stored at -80oC freezer.
The embryo and the de-embryonated grain were ground into a fine powder in liquid
nitrogen. The RNA was isolated from this powder by using SpectrumTM Plant Total
RNA Kit from Sigma Life Science. The RNA was then stored at -80oC until required.
7.2.1.3 cDNA synthesis
The cDNA was synthesized using PhusionTM RT-PCR Kit from Finnzymes. Up to 1g
RNA were combined with 10mM dNTP mix, 1L OligodT primer. This mixture was
brought to 10L by adding RNase-free H2O and then incubated at 65oC for 5 minutes to
denature the RNA. The reaction tubes were then placed on ice. Ten times RT buffer
(2L), RT PCR enzyme mix 2 L and 6L RNase-free H2O were added into these
reaction tubes. The tubes were then put into Hybaid PCR express thermal cycler, with
conditions as follows: primer extention at 25oC for 10 minutes, cDNA synthesis at40oC
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for 30 minutes, and reaction termination at 85oC for 5 minutes. The samples were then
cooled at 4oC.
7.2.2 Degenerate primer design to amplify CGT and F2H sequences in
bread wheat
7.2.2.1 Source of CGT and F2H protein sequences
The sequences used in the alignments for designing the degenerate primers were
obtained from various sources. Protein sequences of the CGT candidate genes were
obtained from Gramene databases (www.gramene.org). Japonica rice sequences
(chapter VI) were used as anchor sequences to locate the syntenic locus in
Brachipodium distacyon, Sorghum bicolor, Zea mays and Indica rice. The wheat
sequence BJ215997 was obtained through BLAST search facility in Plant expression
database website (http://www.plexdb.org/plex.php?database=Wheat).
The homologue F2H and Isoflavone synthases (IFS) protein sequences were obtained
from NCBI database (www.ncbi.nlm.nih.gov/) through BLAST search facility. The rice
F2H sequence (LOC_Os06g01250) identified in chapter VI was used as query. Other
protein sequences of enzymes that work with naringenin as substrate in the flavonoid
pathway were obtained from NCBI databases and previous studies by Asenstorfer et al.
(2007), Ayabe & Akashi (2006), Cummins et al. (2006), Lepiniec et al. (2006), Martens
& Forkmann (1999), Shirley (1998) and Shirley (2001). The unpublished wheat F3H
sequences were provided by Dr. Judy Rathjen.
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7.2.2.2 Sequence alignments
The multiple sequence alignments of CGT (Figure 7.1) and the F2Hs (Figure 7.2) were
performed by MAFFT engine (http://www.ebi.ac.uk/Tools/msa/mafft/) with blossum62
matrix, gap open penalty 1.53 and gap extension penalty 0.123. The alignment was then
transferred to GeneDoc version 2.7 (http://www.nrbsc.org/gfx/genedoc/) for further
multiple alignments editing, shading and primer design. The percentage identity were
analysed by clustalW2.
7.2.2.3 Primer design
Primer pairs for amplification of the CGT
Six degenerate primers were designed from the multiple alignments of rice OSCGT and
translated protein sequences of the CGTs of other cereals and wheat EST BJ215997
(Figure 7.1). Three of the primers were forward primers (F1, F2, F3) and three were
reverse primers (R1, R2, R3) (Table 7.1). Eight pairs of these degenerate primers were
tested in the PCR optimisation. Assuming that the CGT protein sequence for wheat is
similar to that of rice, CGT bands were expected at 1074bp for F1 and R1 primer pairs
(CGTF1R1), 1008bp for F2 and R2 primer pairs (CGTF2R2), 1017bp for F1 and R2
primer pairs (CGTF1R2), 1065bp for F2 and R1 primer pairs (CGTF2R1), 564bp for F2
and R3 primer pairs (CGTF2R3), 576bp for F1 and R3 primer pairs (CGTF2R3), and
480bp for F3and R2 primer pairs (CGTF3R2), using cDNA as template.
Primer pairs for amplification of the F2H
The conserved regions of F2H and IFS protein sequences were identified by placing
these sequences into 2 different groups with different shading colour: the conserved
sequences of IFS were highlighted in green, while the contrasts between F2H/FS2
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against IFS sequences groups were shaded in purple. The conserved regions of both
groups are in black (Figure 7.2). The primers were designed in the sequences with black
and purple shading colour, to minimize amplification of IFS templates.
Due to time constrains, only the amplification of CGT sequence by the degenerate
primers was studied. The directions for further experiments in the future to obtain
optimum CGT amplification methods are proposed.
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Figure 7.1 Multiple alignments of translated protein of putative CGT: LOC_Os06g18010 (Japonica rice OSCGT, Brazier Hicks et al. 2010),
Os06g0288300 (Indica rice glycosyltransferase), BRADI1G43410 (Brachypodium distachyon glycosyltransferase), Sb10g010640 (Sorghum bicolor
glycosyltransferase), GRMZM2G162783 (Zea mays glycosyltransferase) and BJ215997 (wheat EST homologous to rice C-glycosyltransferase). Blue
arrows showed the position of the degenerated primers: F1, F2, and F3 are forward primers, while R1, R2 and R3 are reverse primers. The red lines in
dash are the start and end of the primer sequences. The grey and black shades showed the sequence conservation.
F1F2
F3
R3
R2 R1
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Figure 7.2 Multiple alignments of translated protein of putative F2H, FS2 and IFS: LOC_Os06g01250 (Japonica rice F2H, Du et al. 2010), FS2Mt (Medicago
truncatula F2H, Zhang et al. 2007), F2HGe (Glycyrrhiza echinata F2H, Akashi et al. 1998), F2HCs (Camellia sinensis FS2 (O. Kintze, unpublished-NCBI
F1
F2 and R1
F3 and R2
R3
Cyt 450
168
database)), IFSPs (Pisum sativum IFS, Cooper 2005), IFSTp (Trifolium pratense IFS (Kim et al.
2005, unpublished-NCBI database)), IFS2Vu (Vigna unguilata IFS2, Kaur & Murphy 2010),
IFSPm (Pueraria montana var. lobata IFS, Jeon and Kim (unpublished-NCBI database)). The
F2H and IFS sequences are sorted into 2 different groups: the conserved sequences of IFS are
highlighted in green, while while the contrasts between F2H/FS2 against IFS sequences groups
are shaded in purple. The conserved regions of both groups are in black. Blue arrows show the
position of the degenerate primers: F1, F2, and F3 are forward primers, while R1, R2 and R3
are reverse primers. The red boxes are the position of the primers: F1-F3 are forward primers,
while R1-R3 are reverse primers. The blue arrow and red lines in dash between 471-481kb are
the start and end of the cystein heme-iron ligand signature of the cytochrome P450 protein
motif.
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Table 7.1 Degenerate Primers to amplify CGT in bread wheat
Table 7.2 Degenerate Primers to amplify F2H sequences in bread wheat
7.2.3 Amplification of CGT sequence from wheat gDNA and cDNA by
the degenerate primer pairs
7.2.3.1 Optimization of PCR
Initially, each degenerate primer pair was used to amplify 1.5 ng/L gDNA template of
Nipponbare rice to optimise the PCR conditions. The first PCR master mix used
consisted of 1X PCR buffer, 0.2mM dNTP mixture, 1.5mM MgCl2, 0.2 M Forward
and reverse primers, 5.0 unit Platinum® Taq DNA polymerase (Invitrogen), and water in
a total of 50 L reaction for 6 PCR reactions. The PCR amplification was performed by
using Hybaid PCR express thermal cycler with 12 column x 8 rows gradient blocks with
samples in every odd block number. The PCR condition was as follows: 94oC for 5
minutes of the first cycle, followed by 40 cycles of the second cycle with 94oC
Candidate Genes No Amino acid sequence
Reverse (R)/ Forward (F) Primer sequences
CGT 1 PSAGMGH F1 CCIWSIGCIGGNATGGGNCA2 MGHLVPF F2 ATGGGICAYYTIGTNCCNTT3 PQALHDP F3 CCICARGCIYTICAYGAYCC4 HCGWNSV R1 GTIACISWRTTCCAICCRCARTG5 WVDQEEV R2 AYIKCYTCYTGITCNACCCA6 QFVANGR R3 CKICCRTTIGCIACRAAYTG
Candidate Genes No Amino acid sequence
Reverse (R)/ Forward (F) Primer sequences
F2H 1 PIIGHMHM F1 CCIATHATHGGICAYATGCAYATG2 AFAPYG F2 GCITTYGCICCITAYGGI3 MDFFTAG F3 ATGGAYTTYTTYACICGIGCI4 AFAPYG R1 CCIATYGGICGIAAYCGI5 MDFFTAG R2 CCIGCITGIAAYAAYCTYTAC6 MQEVPA R3 GCI GGI CAY CTR GTR TAC
170
denaturation for 30 seconds, 30-45oC gradient of annealing temperature range for 30
seconds, and 72oC extension for 2 minutes, and ended the PCR cycle with 72oC for 10
minutes. The amplified fragments were then visualised by gel electrophoresis (100mV,
40 minutes) with 1% Agarose and 0.015L/mL Invitrogen SYBR® SafeDNA gel stain
in 1X TBE buffer (0.09M Tris, 0.09M boric acid, and 2 mM EDTA pH 8.0).
The optimum PCR condition and master mix composition were then used to amplify 8
ng/L DNA template (gDNA and cDNA) of nullisomic-tetrasomic lines of Chinese
Spring group 7, Sunco and Tasman parents, Sunco and Tasman panel lines, water as
negative control and the Nipponbare rice as the positive controls. Further optimisations
were performed by modification of master mix composition, especially with the types
and amount of Taq polymerases; the amount of and MgCl2 and the amount of gDNA
and cDNA that were used.
7.2.3.2 Isolation and purification of prospective CGT DNA bands
Firstly, the PCR bands obtained with the right size were re-visualised by gel
electrophoresis with 1X TAE buffer (0.04 M Tris, 1 mM EDTA pH 8.0). The gel was
then viewed over blue light. The visible bands with the expected size were excised by
using blade or stabbed by using 200L pipette tips and then were put into separate
tubes.
Secondly, the DNA from the gel was purified by QIAquick® Spin purification Kit. To
evaporate the excess ethanol, the purified DNA sample tubes were placed in a 37oC hot
block for 10 minutes. The purified DNA obtained was again visualised in 1-1.2%
Agarose gel with 0.015mL/mL Invitrogen SYBR® SafeDNA gel stain in TBE buffer,
171
100mV, 40 minutes. The DNA concentration was measured using Nano-drop
spectrophotometer (Thermo Scientific, USA).
7.2.3.3 Cloning and sequencing of prospective CGT DNA bands
Cloning of prospective DNA bands in pDrive cloning vector
The purified DNA bands were cloned in pDrive cloning vector using QIAGEN® PCR
cloning Kit. To ligate the purified DNA band with the pDrive plasmid cloning site, 1-
4L of purified PCR products was mixed with 50 ng of pDrive cloning vector and 1X
ligation master mix. The mixture was then keep at room temperature (23oC) for 10
minutes and stored at 4oC overnight.
Transformation of p-Drive recombinant plasmid into Escherichia coli
The transformation was performed by electroporation. One l of ligation product was
mixed gently with the E. coli competent cells. Then, 60 L of the mixture was
transfered into an electroporation cuvet (BioRad, USA) and incubated on ice for 5
minutes. The electroporation was performed with 1.8V field strength of electrical pulse,
capacitance of 25F, resistance of 200Ohms, and a pulse length of 4-4.5s. Seven
hundred L SOC medium (containing 2% tryptone, 0.5% yeast extract, 10mML NaCl,
2.5 mM KCl, 10mL MgCl2, 10mM MgSO4, and 20mM glucose) was added to
electroporated cells and then transferred into a fresh tube and stored at 37oC incubator
for 1 hour. The culture was then centrifuged gently at 3500rpm for 2 minutes. The top
500L supernatant was discarded and the remaining of the culture gently resuspended
and poured into Luria broth (LB) media plates containing 0.1 mg/mL ampicilin, 0.03
mg/mL IPTG (isopropylthiogalactoside), and 0.035mg/mL X-gal (5-bromo-4-chloro-3-
indolyl--D-galactopyranoside). The culture plates were stored at 37oC overnight. The
172
white colonies were identified and used to inoculate 2mL in LB liquid media containing
0.1 mg/mL ampicilin and incubated at 37oC in a shaker overnight.
DNA Plasmid isolation and purification
The suspension culture (1.5 mL) was transferred to a new tube and centrifuged at
13000rpm for 5 minutes. The supernatant was removed and the DNA plasmids were
isolated from the bacterial cells using QIAprep® Miniprep Kit. The tubes containing
purified plasmid DNA were then placed in a 37oC hot block for 10-15 minutes to
evaporate the excess ethanol.
To check if the PCR product was successfully inserted into the cloning vector, the
recombinant plasmids were then cut by EcoRI restriction endonuclease enzyme
(Roche). EcoRI enzymes (0.2 units) was mixed with 1X buffer, water and 200 ng of
plasmid DNA and incubated at 37oC for 3-12 hours. The restriction products were
visualised by gel electrophoresis using 1% agarose with 0.015L/mL Invitrogen
SYBR® Safe DNA gel stain in TBE buffer (100mV, 40 minutes). Two band sizes were
expected to be recovered, the pDrive clonning plasmid (3Kb) and the insert PCR
product. The positive purified plasmid samples containing PCR product were sent to
AGRF for Purified DNA sequencing. The BLASTn and BLASTx search was performed
against NCBI databases to identify the function of the protein from the sequencing
results.
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7.2.4 Amplification of CGT sequence from wheat gDNA and cDNA by
nested PCR
To optimise the nested PCR conditions, the wheat gDNA and cDNA were initially
amplified by degenerate primer pairs CGTF1R1 and CGTF2R2 (Figure 7.1) with the
initial condition as explained in section 7.2.3.1. The results were visualised by gel
electrophoresis. The band obtained was excised from the gel and purified as explained
in section 7.2.3.2. Next, the second stage of the nested PCR was performed by re-
amplifying the initial PCR product by CGTF3R2 degenerate primer pairs. For all these
nested PCR amplifications, the rice gDNA and water were used as positive and negative
control respectively.
7.2.5 Optimation of PCR for re-amplification of EcoRI restriction
product
The inserts of PCR product from amplification by CGTF3R2 primer pairs were
recovered from the recombinant plasmids by EcoRI restriction. This sequence was then
re-amplified. The re-amplification by PCR was optimised as explained in the earlier
sections (7.2.3.1).
174
7.3 Results and Discussion
7.3.1 Isolation, purification and cloning of CGT candidate genes for
ACG ratio
7.3.1.1 PCR optimization
PCR with gDNA
At this stage, amplification of the gDNA with the 8 primers pairs was only successfully
optimised with one pair, CGTF3R2. DNA bands with 480kb size were obtained in all of
gDNA of nullisomic-tetrasomic Chinese Spring group 7 (figure 7.3 A and B) indicating
that the primer was not genome specific.
Figure 7.3 A. Results of PCR amplification with primer F3 and R2, DNA of wheat (Chinese
Spring) was used as the template. Lane M: 1 kb plus DNA ladder as marker (100-5000 numbers
in white are their size); Lane 1-6: bands obtained from 35 extension cycles of PCR with
gradient temperature (15oC, every 30 second between 36oC-44oC). B. The results of EcoRI
restriction, when the band resulted from amplification with similar primer pairs with different
wheat DNA samples of nullisomic-tertrasomic lines of Chinese Spring were cloned in p-Drive
cloning vector. The bands at 480bp were the inserts, while the bands at 3.85kb were the p-Drive
vectors. Lane M: 1 kb plus DNA ladder as marker. Lane 1: nullisomic 7B tertrasomic 7D lines,
lane 2, 4 and 5: 7D7B, 3: 7A7B, 6: 7B7A.
100
200
300400500650
8501000
10502000
100
200
300400500650
8501000
10502000
5000
480bp
3.85 kb(p-Drive)
InsertF3R2
1 2 3 4 5 6 1 2 3 4 5 6
A B
M M M M
175
DNA bands with expected size for the product of CGTF3R2 primer pairs (480 kb size)
were also recovered in nested PCR (Figure 7.4 B). However the first stage of nested
PCR amplification with CGTF1R1 did not show any bands (Figure 7.4 A). It is not
clear whether the F1 and R1 primers failed or the amplification was very low. In the
case of F1 and R1 primer failure to amplify the gDNA template, the recovery of
CGTF3R2 product obtained from the amplification of purified gDNA.
Figure 7.4 Results of Nested PCR amplification: A. First stage of PCR amplification by
CGTF1R1 primer pair with Chinese Spring gDNA as template, lane M: 1 kb plus DNA ladder
as marker (numbers in white are in kb size), lanes 1, 3, 4 and 6: amplification products, with red
rectangles showed the position of the expected amplified bands (1050kb), that were excised
prior to purification. B. Second stage of PCR amplification by CGTF3R2 primer pairs with
gDNA of Chinese Spring and rice as template, lane M: 1 kb plus DNA ladder as marker
(numbers in white are in kb size), lane 1: positive control, the band obtained from amplification
of gDNA with CGTF3R2 primer pair without the first stage nested PCR amplification, lane 2
and 3: bands obtained after 2 stages of nested PCR amplification of Chinese Spring gDNA
template with CGTF1R1and CGTF3R2 primer pairs, lane 4 and 5: bands obtained after 2 stages
of nested PCR amplification of rice gDNA template with CGTF1R1and CGTF3R2 primer pairs.
PCR using a cDNA template
The optimisation of PCR with the cDNA successfully amplified products with
CGTF3R2, CGTF2R2 and CGTF1R2 primer pairs (Figure 7.5 A and B). Only one
100
200300400500650850
1000
10502000
5000
100200300400500650850
1000
10502000
5000
480kbF3R2
1 2 3 4 5 6 M M 1 2 3 4 5 6 M MA B
176
reverse primer functioned successfully, the R2 primer at the end of C-terminal of the C-
glycosyltransferase. These results were obtained with the cDNA generated from mRNA
of Sunco and Tasman embryos, Sunco seed coat and gDNA of Chinese Spring wheat
and rice.
Amplification by the degenerate primers with cDNA but not with the gDNA might
indicate that optimum PCR conditions have not been met for PCR with the gDNA.
Alternatively, there might be differences in the exon-intron arrangements between rice
and wheat. There is no intron in the rice CGT sequence, but this does not necessarily
apply to the gene in wheat. In addition, this might also be caused by the high sequence
copy numbers in the wheat genome and high variation in the gDNA, that codes for
glycosyltransferase sequences.
177
Figure 7.5 Results of PCR optimisation for CGTF3R2, CGTF2R2 and CGTF1R2
primer pairs with cDNA as template. The cDNA were constructed from mRNA isolated
from embryo and seed coat of Sunco and Tasman parents. A. PCR optimized for
CGTF3R2 primer pair. cDNA templates: 1,2: Sunco embryo; 3-4: Tasman embryo; 5-6:
Sunco seed coat; 7 and 8 were rice and Chinese Spring wheat as positive controls
respectively; 9: water as negative control B. PCR optimized for CGTF2R2 (2-6, 11, 12)
and CGTF1R2 (7-10, 13, 14) primer pairs. cDNA templates: 2, 7: embryo of Sunco; 3,
8: embryo of Tasman; 4, 9: seed coat of Sunco. Rice (5 and 10) and Chinese Spring
DNA (6) were used as positive controls. M: DNA ladder marked with kb in white.
100
200
300
400500
650
8501000
10502000
F3R2
M 1 2 3 4 5 6 7 8 9 A M 1 2 3 4 5 6 7 8 9 10
100
200
300400500650850
1000
10502000
F2R2 F1R2
B
178
Re-amplification of PCR products of CGTF3R2 primer pairs with cDNA template from
Sunco and Tasman embryo
To recover more products for further analyses, PCR amplification was repeated with
F3R2 following EcoRI restrictions. The results are shown in figure 7.6. Very faint
bands were recovered.
Figure 7.6 Results of re-amplification of PCR products of CGTF3R2 primer pairs with
cDNA template of mRNA from embryo of Sunco (1, 2) and Tasman (3, 4). M: DNA
ladder marked with kb in white).
7.3.1.4 Sequences obtained from the amplification
The purified DNA sequencing results of PCR amplification by gDNA and cDNA using
F3R2 primer pairs were shown in Figure 7.7, 7.8 and 7.9. The translated protein and
DNA sequences from this amplification are similar for all clones. However, none these
sequences (protein and DNA) corresponded to CGT; except for the forward (F3) and
reverse (R2) degenerate primer sequences. The F3 primer sequences (Table 7.1) were
100
200
300
400
500
650
8501000
10502000
M 1 2 3 4
480bpF3R2
179
recovered from the 1st 5‟-3‟ frame translation (Figure 7.8), while the R2 sequences
(Table 7.2) were recovered from the 2nd 5‟-3‟ frame translation (Figure 7.9).
The shift in the 5‟-3‟ frame translation of wheat sequences were also observed with
BJ215997 EST sequence translation that was used in the designing the degenerate
primers. This EST sequence was short and only covers half length of the CGT
sequence. Error and unidentified peaks in the previous sequencing report might cause
this translation shift.
The results of BLAST search of the translated protein and DNA sequences of
CGTF3R2 amplification recovered sequences of transposons in wheat 3B chromosome
BAC library (92-94% similarity, covered 83-93% coverage of query sequences) (Table
7.3). Several coding sequences of this transposable element had putative
glycosyltransferase like functions in Brachypodium distachyon (Table 7.3). However,
the similarity between this putative glycosyltransferase HGA-like and C-
glycosyltransferase DNA sequences are low, only ranged between 44-67% of sequence
identity which covers 85-100% of the query sequences.
180
Figure 7.7 Multiple alignments of DNA sequences, obtained from PCR amplification
with genomic DNA template (sequences coded wheat1) and cDNA template (sequences
coded wheat2 and rice2). Sequence codes: sequence1, sequence2, sequence3,
sequence4, sequence5 and sequence6 indicated the identification of the E.coli clones.
The sequences in the blue rectangle show the position of the F3 and R2 primer in each
sequence. The grey and black shades show the sequence conservation. Alignment was
performed by MAFFT online alignment tools in http://www.ebi.ac.uk.
181
Figure 7.8 Multiple alignment of translated protein sequences, which nucleotides obtained from PCR amplification with gDNA template
(sequences coded wheat1) and cDNA template (sequences coded wheat2 and rice2). Sequence codes: sequence1, sequence2, sequence3,
sequence4, sequence5 and sequence6 indicated the identification of the E.coli clones. The amino acid sequences in the blue rectangle show the
position of the F3 primer in each sequence. The grey and black shades show the sequence conservation. Alignment was performed by MAFFT
online alignment tools in http://www.ebi.ac.uk.
182
Figure 7.9 Multiple alignment of translated protein sequences, which nucleotides obtained from PCR amplification with gDNA template
(sequences coded wheat1) and cDNA template (sequences coded wheat2 and rice2). Sequence codes: sequence1, sequence2, sequence3,
sequence4, sequence5 and sequence6 indicated the identification of the E.coli clones. The amino acid sequences in the blue rectangle show the
position of the R2 primer in each sequence. The grey and black shades show the sequence conservation. Alignment was performed by MAFFT
online alignment tools in http://www.ebi.ac.uk.
183
Table 7.3 Results of megablastn into nucleotide collection. DNA sequences (figure 7.4) were used as query sequences.
-
Plants Locus Function Similarity(%)Coverage (%)FN564432.1 Triticum aestivum chromosome 3B-
specific BAC library, contig ctg0616b 94 86
AM932686.1 Triticum aestivum 3B chromosome, clone BAC TA3B95G2 93 93
FN564434.1 Triticum aestivum chromosome 3B-specific BAC library, contig ctg0954b 92 83 Brachypodium distacyon Bradi3g28010.1 xyloglucan galactosyltransferase 61 97
Bradi2g01350.1 fructose-bisphosphate aldolase 94 100Bradi2g25170.1 glutathione S-transferase, putative 73 97Bradi2g01370.1 phosphatidylserine synthase 96 97Bradi2g01380.1 glycosyltransferase, HGA-like 67 100Bradi2g01390.1 glycosyltransferase, HGA-like 73 100Bradi3g37830.1 glutamate decarboxylase 87 100Bradi2g01420.1 glycosyltransferase, HGA-like 59 100Bradi2g01420.1 glycosyltransferase, HGA-like 64 100Bradi2g01480.1 glycosyltransferase, HGA-like 66 100Bradi4g00290.1 sodium/hydrogen exchanger 82 100Bradi2g14950.1 anaphase-promoting complex subunit 93 85Bradi2g25450.1 glycosyltransferase, HGA-like 44 86Bradi2g40020.1 exonuclease 57 100Bradi2g01510.1 alanyl-tRNA synthetase 83 100Bradi1g24340.1 cytochrome P450 74 99
Genebank accession
Putative functionContig Similarity (%)Coverage (%)
184
7.3.2 Proposed Future work
7.3.2.1 Identification of more Wheat EST sequences
More wheat ESTs (Table 7.4) were obtained from various sources. One EST was
obtained through BLAST search facility in Plant expression database website
(http://www.plexdb.org/plex.php?database=Wheat), two EST sequences were obtained
through BLAST searches in NCBI databases, while the other two sequences were
obtained from wheat GlycosylTransferase Inventory database (GTIdB,
http://wwwappli.nantes.inra.fr:8180/GTIDB/). The exon sequence of LOC_Os06g18010
was used as query for these searches. The predicted protein sequences from these wheat
ESTs were obtained through ExPASy DNA/RNA translation engine
(http://web.expasy.org/translate/).
7.3.5.2 Putative function of the wheat EST sequences
Predicted protein sequences of 4 more wheat ESTs were aligned with amino acid
sequence of the rice CGT. They are similar to the rice sequence with 39-62% ID (Table
7.5). These proteins putatively function as CGT, but they are short, only 219-278 amino
acids, in comparison to that of rice (471 amino acids). Two sequences, CA699411 and
CV773251 were similar to the N-terminal of the CGT (Figure 7.10). The other 2
sequences, CJ606538 and CJ711440, aligned well with the C-terminal of the rice CGT
(Figure 7.11).
185
Table 7.4 Information on the wheat ESTs that were used to design primers for targeting CGT sequence(s) in bread wheat.
Table 7.5 Similarity between wheat ESTs that were used to design primers for targeting CGT sequence(s) in bread wheat and rice CGTs.
Source DbEST id EST name Gene bank Accession
Plant TA accession
Clone Info Wheat cultivar Tissue
PLexdB 11993314 BJ215997 BJ215997 BJ215997 wh9f13 (3') Chinese Spring spike at NCBI 26355865 FGAS067647 CV773251 CV773252 WEF077 Row F column 19 Norstar Crown and NCBI 15514241 wlk8.pk0017.g5 CA699411 CA699412 wlk8.pk0017.g5 (5' end) Stephens leaf
TIGR/GTIdB 38843062 CJ711440 CJ711440 TA105202_4565 whv3n8j04 (5') Valuevskaya shootTIGR/GTIdB 38786813 CJ606358 CJ606358 TA105202_4565 rwhv3n8j04 (3') Valuevskaya shoot
Sequence 1
Length Sequence 2 Length ScoreBJ215997 395 LOC_Os06g18010 471 39CA699411 219 LOC_Os06g18010 471 43CJ606358 230 LOC_Os06g18010 471 62CJ711440 278 LOC_Os06g18010 471 62CV773251 272 LOC_Os06g18010 471 57
186
Figure 7.10 Alignment of protein sequences of wheat ESTs CA699411and CV773251 that have similarity to the N-terminal domain of rice
CGT.
187
Figure 7.11 Alignment of protein sequences of wheat ESTs BJ215997, CJ606358, and CJ711440 that have similarity to the C-terminal
domain of rice CGT.
188
7.3.5.3 Rapid amplification cDNA ends (RACE)-PCR or
chromosome/subgenome walking to obtain the full sequence of CGT
from wheat ESTs
The EST sequences are short and only covered the exons. It requires other methods
such as RACE-PCR and/or genome walking to obtain the full genomic sequences of
the EST.
RACE-PCR (Life TechnologyTM Protocol-Invitogen)
Firstly, specific degenerate primers could be designed to amplify each EST (at least
to anneal at 300bp from the 5‟ end) and the PCR conditions to amplify these ESTs
from the cDNA with the designed primer need optimised. This could be initiated by
methods described in section 7.2.3. These primers could then be used to synthesize
cDNA prior to purification and tailing at the 3'-end of the cDNA. From the sequence
recovered, another nested primer located within the cDNA could be designed to
obtain the full sequence of the EST, either towards the 5‟-3‟ prime end or towards 3‟-
5‟ prime end, and RACE-PCR performed.
Chromosome/subgenome walking
The application of the genome walking protocols is very difficult with bread wheat
due to the complexities of its genome. The large size of hexaploid wheat genome
with high numbers of repetitive sequences, make it is very difficult to walk for a
quite large genomic fragment, up to 1 megabse, while restricting it to a specific
genome region (chromosome) (Feuillet et al. 2003). This method would require a
high resolution map, and a large insert library, which has not yet completed for all
189
hexaploid chromosomes of bread wheat (Stein et al. 2000, Yan et al. 2003).
However, modification of genome walking in a subgenome (A, B or D) of diploid
Triticum and Aegilops wheats have been successful to obtain various genes (Faricelli
et al. 2010, Feuillet et al. 2003, Stein et al. 2000, Yan et al. 2003). To apply
subgenome walking to recover the candidate gene sequence of 7BS QTL for ACG
traits, require diploid wheat BAC library with 7B chromosome from Aegilops
speltoides. To avoid the chromosome walking being stopped by high number of
repeated sequences, BAC of rice and Brachypodium should also be used at the same
time (Faricelli et al. 2010, Feuillet et al. 2003, Stein et al. 2000, Yan et al. 2003). In
addition, specific probe or PCR primers for the candidate genes will also be required
to screen the BAC library.
Specific primers and optimum PCR conditions for amplification of the candidate
genes or ESTs with the CGT candidate genes putative function, and/or for markers
flanking 7BS QTL locus is very crucial for the application of PCR based genome
walking methods. Having highly specific primer pairs and optimum PCR conditions
for the candidate genes of carotenoid biosynthesis, Howitt et al. (2009) successfully
isolated the candidate gene sequences with PCR based genome walking method from
hexaploid bread wheat cultivar Chinese spring.
7.4 Conclusion
The preliminary trial of PCR based methods to amplify the CGT genes from genomic
DNA and cDNA of bread wheat faced significant challenges due to the high
variation in glycosyltransferase sequences in plants as well as the complexity in
190
wheat genome due to its large size and high number of repetitive sequences.
Although sequences with putative glycosyltransferase like function were identified,
this experiment is still in-conclusive because of these challenges. Further
optimization of the PCR with the existing degenerate primers for the genes and ESTs
should be continued. After the specific primers and optimum PCR conditions are
optimised, the experiment could be continued with RACE-PCR and subgenome
walking to obtain the full sequence of the candidate genes. Similar process could also
be applied to F2H.
191
Chapter VIII: General Discussion
8.1 Proposed genetic control of ACG biosynthesis in bread wheat
grain
The strong correlation between amounts of ACG1, ACG2 and total ACG, and the
lack of significant correlation between ACG content and ACG1/ACG2 suggests that
genetic mechanisms that control total ACG content act prior to the glycosylation
steps in biosynthesis. Variation in ACG content could reflect the relative activity of
the enzymes located early in the flavonoid pathway, competition with other branches
of the pathway for flavone precursors and/or UDP sugars, or possibly regulation of
flavonol-2-hydroxylase, the first committed step in the proposed branch in the
flavonoid biosynthesis pathway leading to ACG. A lower content was previously
associated with lower activity of enzymes such as chalcone isomerase, an enzyme
catalyzing an early step in flavonoid biosynthesis (Kashem & Mares 2002).
Variation in the ACG ratio provides a means for investigating on the mechanisms
and regulation of C-glycosylation. No ACGs containing the same sugar residue at
both C6 and C8 were identified and each ACG isomer contained arabinose attached
to either of these carbons. Since changing the ratio did not affect total ACG content,
it seems possible that the proportions of ACG1 and ACG2 depended on either the
relative sizes of the available pools of UDP-glucose and UDP-galactose, the activity
of the epimerase that catalyses their inter-conversion or variation in the activity and
specificity of the C-glycosyltransferases. Different alleles of genes coding for C-
hexosyltransferase may result in differences in UDP-sugar recognition.
192
Elimination of chromosome 7B in Chinese Spring 7B nullisomic lines resulted in an
increase in ACG1/ACG2, i.e. a relative increase in the glucose-containing isomer,
possibly indicating the presence of a C-glycosyltransferase on 7B with specificity for
UDP-galactose. A similar phenotype in the high ratio cultivars could be explained by
a deletion or mutation of a gene controlling this enzyme.
Major QTL were detected at 7BS, whilst minor QTL which co-located with QTL for
grain size were detected at 4B. The 7BS QTL was identified at the same position
after the fine mapping. Alignment of wheat 7BS with the physical maps of rice and
Brachypodium distacyon was used to identify potential candidate genes that could be
involved in control of ACG composition included: a sugar transporter that could
determine the relative sizes of the available pools of UDP-glucose and UDP-
galactose, an epimerase that might function in inter-conversion of these sugars and
glycosyltransferases possibly invovled in the UDP-hexose sugar transfer to the A
flavone ring. In addition, a F2H that might control the total ACG was also identified
on the same chromosome. The model of genetic control based on these finding and
showing possible homologous genes from rice, is proposed in Figure 8.1.
193
Figure 8.1 Proposed model for ACG biosynthesis in bread wheat grain. The rice genes are shown in red.
Glucose-galactose epimerase/Xylose-arabinose
Direct reversible conversion of glucose to galactose
LOC_Os08g0357 (Chr 8)
Glucose/galactosetransporter from
cytoplasm to golgiaparatus/ endoplasmic
reticulumC-glycosyltransferase
Promiscuous, can recognise both glucose
and galactose
LOC_Os06g1801 (Chr 6)
membrane of endoplasmic reticulum or golgi aparatus
Golgi aparatus?LOC_Os08g01410 (Chr8)
Provide glucose/galactose and Xylose-arabinose
by direct conversion
Provide glucose/galactoseby membrane transfer
Lumen of endoplasmic reticulum or golgi aparatus
cytosol
Endoplasmic reticulum?LOC_Os06g3926 (Chr 6)
ACG
194
8.2 Implication of the proposed genetic control for future study and
application of the ACGs
ACGs contribute to yellow colour of YAN in an additive manner with lutein. In
comparison with lutein, the ACGs are present in higher concentration but have lower
coefficient of extinction. Increasing concentration could potentially increase YAN b*
without impacting on use for other end products and reduce the need for colour
additives in some commercial products. However, the level of genetic variation
showed in this study is not sufficient to achieve the yellowness of commercial
noodles and there is also no significant correlation between total ACG content and
yellowness of YAN (b*) due to the low recovery of ACGs in the flour after milling.
The recovery of the ACGs in the flour after milling was influenced by the physical
properties of the grain and their location in outer parts of the grain (bran and pollard
tissue) which are discarded during milling. The removal of these parts from
endosperm during milling is influenced by the grain softness/hardness and moisture
pre-conditioned before milling. This was also confirmed in the results of experiment
with the F1 generations of Sunco/Tasman and Gamut/Reeves when the grains were
dissected and the ACG were analyses from different tissues obtained. No ACG has
been found in the endosperm.
Future options for increasing ACG concentration for YAN might include:
incorporation of embryo to the flour after milling and genetic modification of bread
wheat to achieve ACG expression in the starchy-endosperm. As the ACGs have also
been reported as feeding resistant for brown plant hopper in rice cropping system,
195
and the candidate genes identified, they also can be studied in rice to developed
brown plant hopper resistant rice varieties through breeding and biotechnology.
196
Supplemental materials
197
Supplemental material 3.1 ACG concentration (g/g) (analysed from the grains)
for parents of existing doubled haploid populations. Bars represent SE of means.
From the top to the bottom: ACG1 concentration, ACG2 concentration and Total
ACG concentration
0.020.040.060.080.0
100.0120.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
ACG1 concentration
(g/g)
Parent lines
0.020.040.060.080.0
100.0120.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
ACG2 concentration
(g/g)
Parent lines
0.020.040.060.080.0
100.0120.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
Total ACG concentration
(g/g)
Parent lines
198
Supplemental material 3.2 ACG content in the grain (g/grain) of parents of
existing doubled haploid populations. Bars represent SE of means. From the top to
the bottom: ACG1 content, ACG2 content and total ACG content.
0.0
2.0
4.0
6.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
ACG1 content (g/grain)
Parent lines
0.0
2.0
4.0
6.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
ACG2 content (g/grain)
Parent lines
0.0
2.0
4.0
6.0
Sunc
oTa
sman
Sunc
oA
roon
a
Cran
broo
kH
alber
d
Avoc
etA
ngus
SUN
325B
QT7
475
Avoc
etSu
nvale
Sunv
aleSu
nfiel
d
Total ACG content
(g/grain)
Parent lines
199
Supplemental material 3.3 ACG composition (ACG1/ACG2 ratio) in grain of
parents of existing doubled haploid populations. Bars represent SE of means.
0.00.20.40.60.81.01.2
Sunc
oTa
sman
Sunc
oA
roon
a
Cra
nbro
okH
albe
rd
Avo
cet
Ang
us
SUN
325B
QT7
475
Avo
cet
Sunv
ale
Sunv
ale
Sunf
ield
ACG1 /ACG2 Ratio
Parent lines
200
Supplemental material 3.4 Layout of Sunco/Tasman doubled haploid population trial at Narrabri, New South Wales, Australia. The
Sunco and Tasman parent lines were planted alternately, as one plot for every 20 plots of doubled haploid lines. Information on this layout
was provided by Assoc. Prof. Daryl Mares.
A. Layout for the old lines (147 lines on the revised genome map).
Sunelg Sunelg Sunelg Sunelg Sunelg Sunelg Sunelg 173 172 171 170 169 168 167 166 165 164 163145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 Tasman 162144 143 142 Sunco 140 139 138 137 136 135 134 133 132 131 130 129 128 127109 110 111 112 113 114 115 116 117 118 119 120 Tasman 122 123 124 125 126108 107 106 105 104 103 102 Sunco 100 99 98 97 96 95 94 93 92 9173 74 75 76 77 78 79 80 Tasman 82 83 84 85 86 87 88 89 9072 71 70 69 68 67 66 65 64 63 62 Sunco 60 59 58 57 56 5537 38 39 40 Tasman 42 43 44 45 46 47 48 49 50 51 52 53 5436 35 34 33 32 31 30 29 28 27 26 25 24 23 22 Sunco 20 191 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
201
Supplemental material 3.4 Layout of Sunco/Tasman doubled haploid population trial at Narrabri, New South Wales, Australia (continued)
B. Layout for the new lines (108 lines additional lines for the fine mapping)
Sunelg Sunelg Sunelg Sunelg Sunelg Sunelg 314 313 312 311 310 309297 298 299 300 301 302 303 304 305 306 307 308296 295 294 293 292 291 290 289 288 287 286 285273 274 275 276 277 278 279 280 Tasman 282 283 284272 271 270 269 268 267 266 265 264 263 262 Sunco249 250 251 252 253 254 255 256 257 258 259 260248 247 246 245 244 243 242 Tasman 240 239 238 237225 226 227 228 229 230 231 232 233 234 235 236224 223 222 Sunco 220 219 218 217 216 215 214 213201 202 203 204 205 206 207 208 209 210 211 212
202
Supplemental material 3.5 The frequency distribution of ACG1/ACG2 ratio in 2
sets of Sunco/Tasman doubled haploids. The black lines represent the old population,
the red lines represent additional lines, and the dashed grey lines represent the
distribution of the whole data set. The blue arrows indicate the means of the ratio
trait in the parents (T: Tasman, S: Sunco).
0
10
20
30
40
50
60
70
80
90
100
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
Frequency
Class interval of ACG1/ACG2 ratio distribution
T
S
203
Supplemental material 4.1 List of germplasm and its origin used in this study together with data for ACG1, ACG2 and Total ACG
content (g/g and g/grain); and ACG1/ACG2 ratio.
No Cultivars Origin ACG1 (g/g
ACG2 (g/g
Total ACG (g/g
ACG1 (g/grain)
ACG2 (g/grain)
Total ACG (g/grain)
ACG1/ACG2 Ratio
I Triticum aestivumCultivars from Australian
1 Cunningham Queensland 29.5 62.7 92.2 1.2 2.6 3.9 0.52 EGA Gregory Queensland 15.7 37.3 53.0 0.8 1.8 2.6 0.43 Hartog Queensland 22.6 53.2 75.8 0.9 2.1 2.9 0.44 Janz Queensland 30.3 41.9 72.2 1.3 1.8 3.1 0.75 EGA Hume Queensland 21.5 46.2 67.7 1.0 2.1 3.1 0.56 Kennedy Queensland 14.8 44.7 59.6 0.7 2.2 3.0 0.37 Lang Queensland 33.8 70.9 104.7 1.5 3.1 4.6 0.58 Batavia Queensland 16.1 38.5 54.5 0.7 1.7 2.5 0.49 Baxter Queensland 27.7 35.4 63.1 1.2 1.5 2.7 0.8
10 Spica Queensland 20.5 41.1 61.6 1.3 2.5 3.8 0.511 Tasman Queensland 23.7 58.8 82.5 1.1 2.9 4.0 0.412 Cook Queensland 33.3 32.0 65.3 1.6 1.5 3.1 1.013 Ventura Northern NSW 19.3 51.6 70.9 0.9 2.3 3.2 0.414 Sunvale Northern NSW 39.6 41.2 80.7 1.3 1.4 2.7 1.015 Sunco Northern NSW 45.4 45.9 91.3 2.1 2.1 4.2 1.016 Sunlin Northern NSW 27.3 50.5 77.8 1.2 2.2 3.4 0.617 Gamut Northern NSW 69.8 59.7 129.5 3.0 2.6 5.6 1.218 Yellow Kite Northern NSW 32.1 56.6 88.7 1.3 2.3 3.5 0.619 Sunfield Northern NSW 21.2 40.4 61.6 0.9 1.6 2.5 0.520 Gatcher Northern NSW 31.3 32.8 64.0 1.6 1.7 3.4 1.021 Suneca Northern NSW 24.4 48.2 72.6 1.2 2.4 3.6 0.522 Gabo Northern NSW 60.7 58.3 119.0 2.7 2.6 5.4 1.023 Condor 17 University of Sydney 50.1 44.5 94.6 2.2 1.9 4.1 1.124 Condor 19 University of Sydney 22.0 33.8 55.8 0.7 1.1 1.8 0.725 Diamondbird Southern NSW 13.0 38.2 51.2 0.6 1.7 2.2 0.326 Avocet Southern NSW 31.4 76.4 107.8 1.1 2.6 3.6 0.427 Chara Victoria 17.5 36.9 54.4 0.8 1.7 2.5 0.528 Meering Victoria 23.0 54.8 77.8 0.8 1.8 2.6 0.429 Silverstar Victoria 11.2 31.6 42.8 0.4 1.2 1.7 0.430 Annuello Victoria 17.0 38.9 55.9 0.7 1.7 2.4 0.431 Spear South Australia 27.7 48.4 76.1 1.3 2.2 3.5 0.632 Frame South Australia 27.3 65.4 92.7 1.3 3.1 4.4 0.433 Halberd South Australia 37.1 72.1 109.2 1.6 3.2 4.8 0.534 Krichauff South Australia 20.2 45.1 65.3 0.9 1.9 2.8 0.435 Kukri South Australia 28.9 54.0 82.9 1.5 2.8 4.3 0.5
204
Supplemental 4.1 Germplasm origin and ACG traits (continued)
No Cultivars Origin ACG1 (g/g
ACG2 (g/g
Total ACG (g/g
ACG1 (g/grain)
ACG2 (g/grain)
Total ACG (g/grain)
ACG1/ACG2 Ratio
36 Angus South Australia 35.5 63.6 99.2 1.5 2.7 4.3 0.637 Aroona South Australia 19.9 42.9 62.8 0.9 1.9 2.8 0.538 GBA Ruby Western Australia 21.3 60.0 81.3 1.1 3.1 4.2 0.439 Cascades Western Australia 18.9 42.8 61.8 0.9 2.0 2.9 0.440 Carnamah Western Australia 19.7 43.4 63.1 1.0 2.2 3.2 0.441 Reeves Western Australia 10.8 32.7 43.4 0.5 1.6 2.1 0.342 Westonia Western Australia 18.4 43.8 62.2 0.8 1.8 2.6 0.443 Cranbrook Western Australia 31.2 48.2 79.4 1.6 2.5 4.2 0.644 Canna Western Australia 31.8 61.4 93.2 1.6 3.1 4.7 0.5
Miscellaneous origin45 Seri Mexico 21.1 52.0 73.1 1.1 2.7 3.7 0.446 Ciano Mexico 24.0 35.5 59.5 1.3 1.9 3.1 0.747 AUS1408 South Africa 55.3 88.4 143.7 2.1 3.4 5.5 0.648 Indis South Africa 26.0 44.1 70.1 0.8 1.4 2.3 0.649 SW95-50213 China 14.7 29.7 44.3 0.6 1.3 1.9 0.550 ChuanYu12 China 37.2 88.3 125.5 1.6 3.8 5.5 0.451 ChuanMai18 China 28.8 49.7 78.5 1.2 2.1 3.3 0.652 Jing Hong China 30.6 74.0 104.6 1.9 4.5 6.4 0.453 Haruhikari Japan 23.6 47.2 70.8 1.0 2.0 2.9 0.554 Chinese spring China 52.4 80.7 133.2 2.7 4.1 6.7 0.755 SUN325B Leslie Research Centre, Queensland 26.4 57.4 83.9 1.3 2.7 4.0 0.556 QT7475 Leslie Research Centre, Queensland 23.1 49.0 72.0 1.2 2.5 3.7 0.557 SW95-50213/Cunningham.763 University of Adelaide 35.7 66.9 102.6 1.2 2.2 3.3 0.558 SW95-50213/Cunningham.799 University of Adelaide 27.4 70.8 98.2 0.8 2.1 3.0 0.459 AUS 29565 Mexico 18.7 32.3 51.0 1.0 1.8 2.8 0.660 AUS 29604 Mexico 39.2 71.8 111.0 2.0 3.6 5.6 0.561 AUS 30330 Mexico 40.8 67.7 108.4 2.2 3.7 6.0 0.662 AUS 29572 Mexico 22.7 40.5 63.3 1.2 2.1 3.2 0.663 DM03.122/WI21121.1442 University of Adelaide 23.1 42.8 65.9 1.0 1.8 2.8 0.564 DM03.122/WI21121.1151 University of Adelaide 20.8 35.7 56.6 1.1 1.8 2.9 0.665 DM5686*B12 University of Adelaide 33.7 28.6 62.2 1.2 1.1 2.3 1.266 DM03.24.b.241 University of Adelaide 32.7 44.3 77.0 1.4 1.9 3.2 0.767 DM03.24.b.281 University of Adelaide 30.2 58.5 88.6 1.3 2.5 3.8 0.568 DM03.24.b.248 University of Adelaide 31.1 86.7 117.8 1.2 3.3 4.4 0.469 sunco/Indis.82 University of Adelaide 34.4 47.1 81.5 1.3 1.7 3.0 0.770 AUS1490 University of Adelaide 61.6 104.98 166.6 2.9 4.9 7.8 0.6
205
Supplemental 4.1 Germplasm origin and ACG traits (continued)
No Cultivars Origin ACG1 (g/g sample)
ACG2 (g/g sample)
Total ACG (g/g sample)
ACG1 (g/grain)
ACG2 (g/grain)
Total ACG (g/grain)
ACG1/ACG2 Ratio
Related species71 T. monococcum AUS90416 Australian Winter Cereals Collection, Tamworth, NSW 4.2 22.4 26.5 0.07 0.4 0.5 0.272 T. monococcum AUS90417 Australian Winter Cereals Collection, Tamworth, NSW 1.7 20.6 22.3 0.03 0.3 0.4 0.173 T. monococcum AUS19844 Australian Winter Cereals Collection, Tamworth, NSW 1.2 15.7 16.9 0.02 0.3 0.3 0.174 T. monococcum AUS90359 Australian Winter Cereals Collection, Tamworth, NSW 1.9 21.4 23.3 0.05 0.6 0.6 0.175 T. monococcum AUS90357 Australian Winter Cereals Collection, Tamworth, NSW 3.5 12.3 15.8 0.07 0.3 0.3 0.376 Aegilops tauschii AUS24062 Australian Winter Cereals Collection, Tamworth, NSW 10.6 14.4 25.0 0.08 0.1 0.2 0.777 Aegilops tauschii AUS24091 Australian Winter Cereals Collection, Tamworth, NSW 9.2 11.1 20.4 0.07 0.1 0.2 0.878 Aegilops tauschii AUS23990 Australian Winter Cereals Collection, Tamworth, NSW 17.9 20.8 38.7 0.26 0.3 0.6 0.979 Aegilops tauschii AUS23980 Australian Winter Cereals Collection, Tamworth, NSW 13.8 17.7 31.6 0.17 0.2 0.4 0.880 Aegilops tauschii AUS24048 Australian Winter Cereals Collection, Tamworth, NSW 15.5 22.0 37.5 0.19 0.3 0.5 0.781 Aegilops tauschii AUS22445 Australian Winter Cereals Collection, Tamworth, NSW 24.1 38.6 62.7 1.17 1.9 3.0 0.682 T. uratu AUS27031 Australian Winter Cereals Collection, Tamworth, NSW 4.7 40.5 45.1 0.10 0.9 0.9 0.183 T. uratu AUS26932 Australian Winter Cereals Collection, Tamworth, NSW 5.4 34.3 39.8 0.13 0.8 0.9 0.284 T. uratu AUS26939 Australian Winter Cereals Collection, Tamworth, NSW 4.5 35.4 40.0 0.10 0.8 0.9 0.185 T. uratu AUS26947 Australian Winter Cereals Collection, Tamworth, NSW 1.9 15.3 17.2 0.04 0.3 0.4 0.186 T. uratu AUS26978 Australian Winter Cereals Collection, Tamworth, NSW 6.1 43.9 50.0 0.13 0.9 1.0 0.187 Aegilops speltoides AUS18813 Australian Winter Cereals Collection, Tamworth, NSW 29.6 39.6 69.2 0.14 0.2 0.3 0.788 Aegilops speltoides AUS18995 Australian Winter Cereals Collection, Tamworth, NSW 23.4 52.6 77.9 0.16 0.3 0.5 0.589 Aegilops speltoides AUS20346 Australian Winter Cereals Collection, Tamworth, NSW 34.8 60.4 95.2 0.13 0.2 0.4 0.690 Aegilops speltoides AUS21637 Australian Winter Cereals Collection, Tamworth, NSW 18.3 31.4 49.7 0.24 0.4 0.7 0.691 Aegilops speltoides AUS21640 Australian Winter Cereals Collection, Tamworth, NSW 14.5 28.2 42.7 0.07 0.1 0.2 0.592 Triticum diccocum AUS17641 Australian Winter Cereals Collection, Tamworth, NSW 30.3 78.0 108.3 1.19 3.1 4.3 0.493 Triticum diccocum var rufum AUS21758 Australian Winter Cereals Collection, Tamworth, NSW 31.0 44.3 75.3 1.53 2.2 3.7 0.794 Triticum diccocum var farrum AUS10559 Australian Winter Cereals Collection, Tamworth, NSW 33.1 72.2 105.3 1.08 2.4 3.5 0.595 Triticum dicoccoides AUS17967 Australian Winter Cereals Collection, Tamworth, NSW 44.6 67.0 111.5 2.38 3.6 6.0 0.796 Triticum carthlicum AUS17644 Australian Winter Cereals Collection, Tamworth, NSW 26.7 100.1 126.8 1.33 5.0 6.3 0.397 Triticum polonicum AUS17970 Australian Winter Cereals Collection, Tamworth, NSW 27.0 81.5 108.5 1.31 3.9 5.3 0.398 Triticum polonicum AUS17645 Australian Winter Cereals Collection, Tamworth, NSW 25.8 59.8 85.7 0.99 2.3 3.3 0.499 Triticum turgidum AUS17969 Australian Winter Cereals Collection, Tamworth, NSW 37.2 67.5 104.7 1.61 2.9 4.5 0.6
100 Triticum durum var bellaroi NSW 17.5 54.1 71.6 1.09 3.4 4.5 0.3101 Triticum durum var wollaroi NSW 20.1 33.8 53.9 1.27 2.1 3.4 0.6102 Triticum durum var kalka South Australia 29.8 49.1 78.9 1.55 2.5 4.1 0.6103 Triticum durum var yallaroi NSW 33.5 65.0 98.4 1.51 2.9 4.4 0.5104 Triticum durum var kamilaroi NSW 28.7 56.5 85.2 1.41 2.8 4.2 0.5105 Triticum spelta Australian Winter Cereals Collection, Tamworth, NSW 60.6 118.8 179.4 2.56 5.0 7.6 0.5
* AUS: accession number in Australian winter cereal collection (AWCC)
206
Supplementary material 4.2 Chromatogram obtained for neutral hydroxylamine
extract of T. aestivum cv Sunco. The peaks corresponding to the two types of the
apigenin C-di-glycosides (ACG1 and ACG2) are indicated by arrows.
207
Supplemental material 4.3 100 grain weight, ACG consentration, ACG content
and ratio ofsome variaties that were grown both in the field and in the glass house.
Blue box: in the field; red box: inthe glass house, bars represnt SE of means.
0.001.002.003.004.005.006.00
100grain weight
(g)
0.0030.0060.0090.00
120.00150.00180.00
ACG1
concentration
(g/g)
0.0030.0060.0090.00
120.00150.00180.00
ACG2
concentration
(g/g)
0.0030.0060.0090.00
120.00150.00180.00
Chinese Spring Sunco Sunvale Tasman Triticum spelta
Total ACG
concentration
(g/g)
Varieties
Triticum spelta
208
Supplemental material 4.3 (continued)
0.00
2.00
4.00
6.00
8.00
ACG1 content
(g/grain)
0.00
2.00
4.00
6.00
8.00
ACG2 content
(g/grain)
0.00
2.00
4.00
6.00
8.00
Total ACG
content
(g/grain)
0.00
0.50
1.00
1.50
2.00
Chinese Spring Sunco Sunvale Tasman Triticum spelta
ACG1/ACG2
Ratio
Varieties
Triticum spelta
209
Supplemental material 4.4 Means (+ SE) of total ACG content (g/grain) of
nullisomic (N)-tetrasomic (T) lines Chinese Spring (A) and Chinese Spring/Triticum
spelta substitution lines (B). a-n: a-i: indicate significant differences (p<0.01) in total
ACG content based on Tukey test of multiple comparison at 5% level.
A B Substitution lines
N 1A T 1B 5.75 + 0.80 jklm 1A 7.79 + 0.44 bcdeN 1A T 1D 5.45 + 0.28 ijklm 1B 5.97 + 0.25 abN 1B T 1A 3.74 + 0.06 abcdefghi 1D 8.47 + 0.54 deN 1B T 1D 3.26 + 0.04 abcdefg 2A 6.40 + 0.35 abcdN 1D T 1A 4.01 + 0.11 abcdefghijk 2B 8.23 + 0.81 bcdeN 1D T 1B 4.74 + 0.23 fghijklm 2D 7.81 + 0.16 bcdeN 2A T 2B 5.98 + 0.27 lmn 3A 6.68 + 0.16 abcdN 2A T 2D 3.76 + 0.18 abcdefghi 3B 6.84 + 0.24 abcdeN 2B T 2A 2.99 + 0.14 abcdef 3D 7.95 + 0.50 bcdeN 2B T 2D 2.53 + 0.09 abcd 4A 8.40 + 0.42 cdeN 2D T 2A 4.44 + 0.18 defghijklm 4B 7.56 + 0.40 bcdeN 2D T 2B 4.22 + 0.24 bcdefghijkl 4D 6.66 + 0.06 abcdN 3A T 3B 3.72 + 0.11 abcdefghi 5A 6.12 + 0.26 abcN 3A T 3D 5.10 + 0.39 ghijklm 5B 6.29 + 0.21 abcdN 3B T 3A 5.50 + 0.19 ijklm 5D 6.78 + 0.68 abcdN 3B T 3D 4.26 + 0.21 cdefghijkl 6A 8.16 + 0.26 bcdeN 3D T 3A 4.71 + 0.24 fghijklm 6B 6.62 + 0.16 abcdN 3D T 3B 4.23 + 0.13 cdefghijkl 6D 5.22 + 0.26 aN 4A T 4B 3.43 + 0.76 abcdefgh 7A 6.61 + 0.27 abcdN 4A T 4D 4.35 + 0.46 cdefghijklm 7B 9.10 + 0.98 eN 4B T 4A 4.55 + 0.26 efghijklm 7D 6.20 + 0.42 abcdN 4B T 4D 5.91 + 0.67 klmn Chinese spring 6.74 + 0.32 abcdN 4D T 4A 2.14 + 0.19 a Triticum spelta 7.59 + 0.08 bcdeN 4D T 4B 4.23 + 0.07 cdefghijklN 5A T 5B 3.46 + 0.29 abcdefghN 5A T 5D 3.36 + 0.22 abcdefghN 5B T 5A 4.41 + 0.52 cdefghijklmN 5B T 5D 4.96 + 0.40 ghijklmN 5D T 5A 2.28 + 0.10 abN 5D T 5B 3.42 + 0.19 abcdefghN 6A T 6B 5.28 + 0.20 hijklmN 6A T 6D 5.08 + 0.69 ghijklmN 6B T 6A 2.69 + 0.31 abcdeN 6B T 6D 5.23 + 0.56 hijklmN 6D T 6A 2.50 + 0.24 abcN 6D T 6B 3.93 + 0.21 abcdefghijN 7A T 7B 3.16 + 0.05 abcdefgN 7A T 7D 7.73 + 0.30 nN 7B T 7A 6.21 + 0.45 mnN 7B T 7D 6.13 + 0.39 lmnN 7D T 7A 5.41 + 0.13 ijklmN 7D T 7B 2.59 + 0.21 abcd
5.82 + 0.28 jklmn
Nullisomic-tetrasomic lines of
Chines Spring
Total ACG content
(g/grain)
Chinese spring
Total ACG content
(g/grain)
Supplemental material 4.5 Pedigree of Sunco and its relatives as drawn from (Martynov & Dobrotvorskaya 2006).
210
A NOTE:
This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.
Supplemental material 4.6 Pedigree of Tasman and its relatives as drawn from (Martynov & Dobrotvorskaya 2006).
211
A NOTE:
This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.
212
Supplemental material 5.1 Proportion and ratio of ACG1 and ACG2 in grain and
Quadrumat Junior mill flour.
Ventura 27.2 + 0.3 72.8 + 0.3 0.4 + 0.005 42.7 + 0.3 57.3 + 0.3 0.7 + 0.01Sunvale 49.0 + 0.3 51.0 + 0.3 1.0 + 0.01 56.1 + 0.5 43.9 + 0.5 1.3 + 0.03Sunco 49.7 + 0.4 50.3 + 0.4 1.0 + 0.02 54.7 + 1.6 45.3 + 1.6 1.2 + 0.1Diamondbird 25.3 + 0.5 74.7 + 0.5 0.3 + 0.01 46.9 + 2.3 53.1 + 2.3 0.9 + 0.1Sunlin 35.5 + 2.3 64.5 + 2.3 0.6 + 0.1 43.7 + 0.6 56.3 + 0.6 0.8 + 0.02Cunningham 32.0 + 0.5 68.0 + 0.5 0.5 + 0.01 44.4 + 1.9 55.6 + 1.9 0.8 + 0.1EGA Gregory 29.5 + 2.3 70.5 + 2.3 0.4 + 0.05 50.7 + 2.2 49.3 + 2.2 1.0 + 0.1Hartog 29.9 + 0.7 70.1 + 0.7 0.4 + 0.01 37.4 + 0.5 62.6 + 0.5 0.6 + 0.01Janz 41.9 + 1.2 58.1 + 1.2 0.7 + 0.04 52.2 + 4.1 47.8 + 4.1 1.1 + 0.2EGA Hume 31.7 + 0.4 68.3 + 0.4 0.5 + 0.01 38.4 + 1.1 61.6 + 1.1 0.6 + 0.03Kennedy 24.9 + 0.1 75.1 + 0.1 0.3 + 0.002 37.9 + 0.3 62.1 + 0.3 0.6 + 0.01Lang 32.2 + 0.5 67.8 + 0.5 0.5 + 0.01 45.9 + 0.1 54.1 + 0.1 0.8 + 0.003Batavia 29.4 + 0.6 70.6 + 0.6 0.4 + 0.01 44.0 + 2.6 56.0 + 2.6 0.8 + 0.1Baxter 43.8 + 0.1 56.2 + 0.1 0.8 + 0.004 57.0 + 2.5 43.0 + 2.5 1.3 + 0.1Spear 36.4 + 0.3 63.6 + 0.3 0.6 + 0.01 50.6 + 0.6 49.4 + 0.6 1.0 + 0.02Frame 29.4 + 0.1 70.6 + 0.1 0.4 + 0.002 40.9 + 1.1 59.1 + 1.1 0.7 + 0.03Halberd 34.0 + 0.5 66.0 + 0.5 0.5 + 0.01 45.0 + 0.6 55.0 + 0.6 0.8 + 0.02Krichauff 31.0 + 0.3 69.0 + 0.3 0.4 + 0.01 39.1 + 1.1 60.9 + 1.1 0.6 + 0.03Kukri 34.8 + 0.1 65.2 + 0.1 0.5 + 0.003 45.7 + 2.8 54.3 + 2.8 0.9 + 0.1Chara 32.1 + 0.7 67.9 + 0.7 0.5 + 0.01 36.3 + 1.8 63.7 + 1.8 0.6 + 0.04Meering 29.6 + 0.6 70.4 + 0.6 0.4 + 0.01 38.5 + 1.0 61.5 + 1.0 0.6 + 0.03Silverstar 26.3 + 1.6 73.7 + 1.6 0.4 + 0.03 41.4 + 1.8 58.6 + 1.8 0.7 + 0.1Annuello 30.3 + 0.6 69.7 + 0.6 0.4 + 0.01 45.1 + 1.1 54.9 + 1.1 0.8 + 0.04GBA Ruby 26.2 + 0.0 73.8 + 0.0 0.4 + 0.001 39.4 + 1.3 60.6 + 1.3 0.7 + 0.03Cascades 30.6 + 0.3 69.4 + 0.3 0.4 + 0.01 42.7 + 0.2 57.3 + 0.2 0.7 + 0.00Carnamah 31.0 + 0.7 69.0 + 0.7 0.4 + 0.01 45.0 + 1.6 55.0 + 1.6 0.8 + 0.1Reeves 24.8 + 0.7 75.2 + 0.7 0.3 + 0.01 36.2 + 1.9 63.8 + 1.9 0.6 + 0.05Westonia 29.6 + 0.2 70.4 0.2 0.4 0.005 49.6 + 0.5 50.4 + 0.5 1.0 + 0.02MaxMinMeans 32.4 + 3.4 67.6 + 3.4 0.5 + 0.1 44.6 + 3.8 55.4 + 3.8 0.8 + 0.1
75.2 1.024.8 0.3
Proportion in grain (%) Ratio in grain Proportion in flour (%) Ratio in flourACG1
57.0 63.8 1.336.2 43.0 0.650.3
49.7
CultivarsACG1 ACG2 ACG2
213
Supplemental material 5.2 Proportion (%) of Lutein in grain and Quadrumat Junior
mill flour.
Ventura 33.2 + 0.01 25.3 + 0.40 41.5 + 0.40 66.8 + 0.01 23.1 + 0.07 28.9 + 0.10 48.0 + 0.1 76.9 + 0.1Sunvale 35.9 + 0.82 37.8 + 1.32 26.2 + 0.51 64.1 + 0.82 24.9 + 0.08 34.8 + 0.20 40.3 + 0.3 75.1 + 0.1Sunco 33.4 + 0.18 35.0 + 0.18 31.7 + 0.21 66.6 + 0.18 25.6 + 0.13 31.9 + 0.29 42.5 + 0.3 74.4 + 0.1Diamondbird 34.7 + 0.12 29.2 + 0.26 36.1 + 0.24 65.3 + 0.12 24.0 + 0.08 30.8 + 0.03 45.2 + 0.1 76.0 + 0.1Sunlin 30.4 + 0.08 32.3 + 0.12 37.3 + 0.14 69.6 + 0.08 21.5 + 0.06 36.6 + 0.01 41.9 + 0.1 78.5 + 0.1Cunningham 33.4 + 0.27 35.5 + 0.20 31.1 + 0.22 66.6 + 0.27 27.0 + 0.24 36.2 + 0.06 36.8 + 0.3 73.0 + 0.2EGA Gregory 32.2 + 0.21 31.5 + 0.13 36.4 + 0.31 67.8 + 0.21 25.0 + 0.08 34.4 + 0.20 40.6 + 0.3 75.0 + 0.1Hartog 38.3 + 0.39 42.4 + 0.31 19.3 + 0.11 61.7 + 0.39 27.8 + 0.08 33.5 + 0.04 38.7 + 0.1 72.2 + 0.1Janz 32.8 + 0.01 33.9 + 0.14 33.3 + 0.13 67.2 + 0.01 22.7 + 0.18 36.1 + 0.34 41.1 + 0.4 77.3 + 0.2EGA Hume 38.0 + 0.23 31.6 + 0.37 30.4 + 0.14 62.0 + 0.23 25.2 + 0.31 31.3 + 0.19 43.5 + 0.4 74.8 + 0.3Kennedy 30.8 + 0.12 28.8 + 0.25 40.4 + 0.14 69.2 + 0.12 19.1 + 0.04 27.2 + 0.26 53.8 + 0.2 80.9 + 0.0Lang 33.1 + 0.23 35.0 + 0.31 31.9 + 0.13 66.9 + 0.23 23.1 + 0.11 35.1 + 0.33 41.8 + 0.3 76.9 + 0.1Batavia 32.6 + 0.13 34.0 + 0.17 33.3 + 0.09 67.4 + 0.13 24.2 + 0.07 36.6 + 0.22 39.2 + 0.2 75.8 + 0.1Baxter 36.5 + 0.15 32.8 + 0.20 30.7 + 0.22 63.5 + 0.15 25.2 + 0.25 31.3 + 0.12 43.5 + 0.3 74.8 + 0.2Spear 37.4 + 0.02 34.8 + 0.16 27.8 + 0.16 62.6 + 0.02 31.0 + 0.11 34.3 + 0.25 34.6 + 0.2 69.0 + 0.1Frame 40.6 + 0.34 44.0 + 0.14 15.4 + 0.39 59.4 + 0.34 32.2 + 0.06 32.3 + 0.02 35.5 + 0.1 67.8 + 0.1Halberd 38.1 + 0.30 39.7 + 0.44 22.3 + 0.73 61.9 + 0.30 30.2 + 0.08 35.2 + 0.15 34.6 + 0.1 69.8 + 0.1Krichauff 30.9 + 0.07 35.2 + 0.01 33.9 + 0.06 69.1 + 0.07 27.8 + 0.11 37.3 + 0.16 35.0 + 0.3 72.2 + 0.1Kukri 38.2 + 0.37 34.4 + 0.65 27.3 + 0.31 61.8 + 0.37 30.5 + 0.13 37.8 + 0.03 31.8 + 0.1 69.5 + 0.1Chara 32.7 + 0.36 30.2 + 0.45 37.1 + 0.11 67.3 + 0.36 24.3 + 0.19 35.4 + 0.13 40.3 + 0.1 75.7 + 0.2Meering 36.3 + 0.39 28.8 + 0.10 34.9 + 0.31 63.7 + 0.39 26.0 + 0.07 34.5 + 0.06 39.5 + 0.1 74.0 + 0.1Silverstar 39.3 + 0.11 34.5 + 0.10 26.2 + 0.12 60.7 + 0.11 28.8 + 0.08 35.3 + 0.29 35.9 + 0.3 71.2 + 0.1Annuello 31.4 + 0.15 39.5 + 0.46 29.1 + 0.33 68.6 + 0.15 27.0 + 0.07 33.7 + 0.12 39.3 + 0.1 73.0 + 0.1GBA Ruby 35.0 + 0.21 32.1 + 0.28 32.8 + 0.19 65.0 + 0.21 18.9 + 0.08 33.5 + 0.19 47.7 + 0.2 81.1 + 0.1Cascades 33.6 + 0.19 35.2 + 0.20 31.2 + 0.07 66.4 + 0.19 26.7 + 0.05 37.2 + 0.10 36.1 + 0.1 73.3 + 0.1Carnamah 26.4 + 0.37 34.2 + 0.05 39.5 + 0.36 73.6 + 0.37 21.0 + 0.10 31.6 + 0.09 47.4 + 0.1 79.0 + 0.1Reeves 30.5 + 0.36 31.5 + 0.94 38.0 + 0.59 69.5 + 0.36 17.9 + 0.07 31.3 + 0.13 50.8 + 0.2 82.1 + 0.1Westonia 30.1 + 0.03 32.6 + 0.04 37.4 + 0.06 69.9 + 0.03 23.8 + 0.13 33.4 + 0.01 42.8 + 0.1 76.2 + 0.1
MaxMinMeans 34.1 + 0.63 34.0 + 0.77 31.9 + 1.17 65.9 + 0.63 25.2 + 0.68 33.8 + 0.49 41.0 + 1.0 74.8 + 0.7
Lutein-ester
73.6 37.8 53.8 82.1
Proportion in the grain (%) Proportion in the flour (%)Diester Lutein
Lutein-ester Monoester Lutein
31.8 67.826.4 25.3 15.4 59.4 17.9 27.240.6 44.0 41.5 32.2
VarietiesLutein Monoester
Lutein Lutein Diester
Lutein
214
Supplemental material 5.3 ACG content and recovery in Bühler Mill flour fractions.
Break flour
(g/g)
Reduction flour
(g/g)
Bran (g/g)
Pollard (g/g)
Break flour (g)
Reduction flour (g) Bran (g)
Pollard (g)
Krichauff 0.7 2.6 88.8 98.3 3.3 190.4 0.3 6.4 85.6 77.5 6.7 169.8 4.0 96.0Silver star 1.8 2.9 51.2 79.5 4.7 135.4 1.4 9.3 54.5 46.5 10.7 111.7 9.6 90.4Halberd 1.8 6.7 149.3 136.7 8.5 294.5 0.8 13.6 107.4 40.8 14.4 162.6 8.9 91.1Sunco 2.1 6.2 94.2 73.2 8.3 175.7 1.4 20.4 89.9 37.0 21.8 148.8 14.7 85.3Ruby 2.2 5.4 105.2 114.9 7.6 227.7 1.3 16.4 90.4 57.2 17.7 165.3 10.7 89.3Hartog 2.7 2.8 61.8 86.2 5.5 153.5 1.5 6.7 45.2 35.7 8.2 89.0 9.2 90.8Reeves 1.9 5.6 51.1 84.3 7.5 142.9 0.7 12.0 37.7 48.1 12.7 98.5 12.9 87.1Aroona 2.5 10.0 47.7 111.6 12.4 171.8 1.9 31.5 44.2 48.0 33.4 125.6 26.6 73.4Sunvale 1.2 8.2 84.1 146.7 9.4 240.1 0.7 20.3 66.0 61.9 21.1 149.0 14.1 85.9Hume 0.8 2.0 101.9 99.9 2.8 204.6 0.5 5.3 100.8 52.8 5.8 159.5 3.7 96.3Max 2.7 10.0 149.3 146.7 12.4 294.5 1.9 31.5 107.4 77.5 33.4 169.8 26.6 96.3Min 0.7 2.0 47.7 73.2 2.8 135.4 0.3 5.3 37.7 35.7 5.8 89.0 3.7 73.4Rates 1.8 5.2 83.5 103.1 7.0 193.7 1.1 14.2 72.2 50.5 15.3 138.0 11.4 88.6Krichauff 1.0 4.7 128.2 183.3 5.8 317.2 0.5 11.5 123.6 144.5 12.0 280.2 4.3 95.7Silver star 3.4 5.2 113.2 165.6 8.7 287.5 2.7 16.8 120.5 96.8 19.4 236.7 8.2 91.8Halberd 2.1 9.7 222.5 201.1 11.7 435.3 0.9 19.6 160.0 60.0 20.5 240.5 8.5 91.5Sunco 1.7 6.2 70.9 69.4 7.9 148.2 1.1 20.6 67.7 35.1 21.7 124.5 17.5 82.5Ruby 6.7 10.8 270.6 265.4 17.5 553.5 4.0 33.1 232.6 132.1 37.1 401.7 9.2 90.8Hartog 4.7 5.8 148.6 196.4 10.5 355.6 2.7 13.7 108.7 81.2 16.4 206.3 8.0 92.0Reeves 3.6 11.7 106.9 173.6 15.3 295.9 1.3 25.2 78.9 99.1 26.4 204.5 12.9 87.1Aroona 3.8 17.3 98.0 199.7 21.1 318.8 2.9 54.7 90.8 85.9 57.6 234.3 24.6 75.4Sunvale 1.1 8.7 121.3 154.2 9.8 285.3 0.6 21.6 95.3 65.1 22.2 182.6 12.2 87.8Hume 1.3 2.8 145.1 165.9 4.1 315.2 0.9 7.6 143.5 87.8 8.5 239.8 3.5 96.5Max 6.7 17.3 270.6 265.4 21.1 553.5 4.0 54.7 232.6 144.5 57.6 401.7 24.6 96.5Min 1.0 2.8 70.9 69.4 4.1 148.2 0.5 7.6 67.7 35.1 8.5 124.5 3.5 75.4Rates 2.9 8.3 142.5 177.5 11.3 331.2 1.8 22.4 122.1 88.8 24.2 235.1 10.9 89.1Krichauff 1.7 7.4 217.0 281.5 9.1 507.6 0.9 17.9 209.2 222.1 18.7 450.0 4.2 95.8Silver star 5.2 8.2 164.4 245.2 13.4 422.9 4.1 26.1 175.0 143.2 30.2 348.4 8.7 91.3Halberd 3.8 16.3 371.8 337.7 20.2 729.7 1.7 33.2 267.4 100.8 34.9 403.1 8.7 91.3Sunco 3.7 12.4 165.1 142.6 16.2 323.9 2.6 41.0 157.6 72.1 43.6 273.3 15.9 84.1Ruby 8.9 16.2 375.8 380.3 25.1 781.2 5.4 49.4 323.0 189.2 54.8 567.0 9.7 90.3Hartog 7.4 8.6 210.4 282.7 16.1 509.2 4.2 20.4 153.8 116.9 24.6 295.3 8.3 91.7Reeves 5.6 17.3 158.1 257.9 22.8 438.8 2.0 37.2 116.7 147.2 39.1 303.0 12.9 87.1Aroona 6.2 27.3 145.7 311.3 33.5 490.5 4.8 86.2 135.0 133.9 91.0 359.9 25.3 74.7Sunvale 2.3 17.0 205.3 300.8 19.3 525.4 1.4 41.9 161.3 127.1 43.3 331.6 13.0 87.0Hume 2.1 4.8 247.0 265.8 6.9 519.7 1.5 12.9 244.3 140.7 14.3 399.3 3.6 96.4Max 8.9 27.3 375.8 380.3 33.5 781.2 5.4 86.2 323.0 222.1 91.0 567.0 25.3 96.4Min 1.7 4.8 145.7 142.6 6.9 323.9 0.9 12.9 116.7 72.1 14.3 273.3 3.6 74.7Rates 4.7 13.6 226.1 280.6 18.3 524.9 2.8 36.6 194.3 139.3 39.4 373.1 11.0 89.0
Total amount of ACG in
flour fractions (g)
Total amount ACG in all
milling fraction (g)
Recovery in flour
fractions (%)
Recovery in Bran and pollard
fractions (%)ACG1
The amount of ACG (g) in milling fractionsConcentration (g/g) in samples
ACG2
Total ACG content
Total ACG concentration in flour fractions
(g/g)
Total ACG concentration in
grain (g/g)ACG Traits Sample
215
Supplemental material 5.4 Comparison of changes in the L* (YAN-WSN, red
lines and markers) and b* (YAN-WSN, black lines and markers) at 0, 2, 4 and 24
hours. A: Sunvale, B:Sunco, C: Krichauff, D: GBA Ruby, E: Carnamah, F:Reeves.
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
0 2 4 24
Time (hour)-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
0 2 4 24
Time (hour)
-2.0-1.00.01.02.03.04.05.06.07.08.0
0 2 4 24
Time (hour)-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
0 2 4 24
Time (hour)
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
0 2 4 24
Time (hour)-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
0 2 4 24
Time (hour)
A B
C D
E F
216
Supplemental material 6.1 Genetic map of Sunco/Tasman doubled haploid population re-constructed with 361 markers and 153 lines of the
population. The bars next to the 2B, 4A, 4B, 4D and 7B maps show the QTL location: ACG1 concentration (g/g) (dark blue), ACG2
contentration (g/g) (black), ACG1 content (g/grain) (green), ACG2 content (g/grain) (pink), ACG1/ACG2 ratio (brown), 100 grain weight
(red), total concentration (g/g) (gold) and total content (g/grain): bright blue.
217
Supplemental material 6.1 Genetic map (continued)
218
Supplemental material 6.1 Genetic map (continued)
219
Supplemental material 6.1 Genetic map (continued)
220
Supplemental material 6.1 Genetic map (continued)
221
Supplemental material 6.2 QTL for ACG traits and 100 grain weight in Sunco/Tasman doubled haploid population. QTL Test Profiles of the
whole genome scan with cofactors (CIM) function in GENSTAT 14. A. QTL for ACG1 concentration (μg/g), B. QTL for ACG2 concentration
(μg/g), C. Total QTL concentration (μg/g), D. QTL for ACG1/ACG2 ratio, E. QTL for ACG1 content (μg/grain), F. QTL for ACG2 content
(μg/grain) G. QTL for Total ACG content (μg/grain), H. QTL for 100 grain weight (g). For the QTL effect, blue: Sunco effect, red: Tasman effect.
A
D
B
C
222
Supplemental material 6.2 Genome Scan for ACG traits in Sunco/Tasman doubled haploid population (continued).
E
H
F
G
223
Supplemental material 6.3 Analysis of polymorphic markers located on 7BS of
Sunco/Tasman doubled haploid population; ns = not significant; *: significant
(p<0.001, Fpr = 3.841).
Markers 2
1:1 Significance A genotypes B genotypes n missing datagwm400b 3.79 ns 151 119 270 5gwm0297a 0.09 ns 138 133 271 4gwm0131b 0.18 ns 139 132 271 4barc0072 0.03 ns 136 133 269 6BE352570 0.77 ns 103 116 219 56barc0085 0.06 ns 130 134 264 11gwm0046b 0.30 ns 130 139 269 6wmc0426 0.03 ns 133 136 269 6wmc0076 0.02 ns 131 129 260 15sun16 2.99 ns 77 57 134 141gwm573 0.40 ns 64 57 121 154P45/M32-2 0.55 ns 62 54 116 159P40/M36-8 1.23 ns 75 62 137 138wg180b 1.94 ns 83 66 149 126wmc402 2.16 ns 84 66 150 125stm337b 0.46 ns 73 65 138 137wmc0662 0.00 ns 135 134 269 6wmc0335 0.03 ns 135 132 267 8wmc0364 0.09 ns 138 133 271 4gwm0297b 0.00 ns 135 136 271 4BE445287 0.03 ns 70 72 142 133gwm0112a 0.14 ns 130 124 254 21P42/M78 0.56 ns 77 68 145 130P39/M78-1 0.01 ns 70 71 141 134wmc273 2.75 ns 44 61 105 170gwm344 2.28 ns 62 80 142 133gwm577 0.57 ns 52 60 112 163ksuE19 0.77 ns 60 70 130 145rda481 1.46 ns 60 74 134 141gwm0540 1.98 ns 124 147 271 4gwm0276b 82.97 * 60 211 271 4gwm0276a 17.37 * 170 101 271 4gwm0112b 5.59 * 155 116 271 4gwm0293b 60.64 * 70 199 269 6gwm0016 0.50 ns 130 141 271 4ksm0173b 3.67 ns 131 116 247 28wmc0723 6.17 * 156 115 271 4wmc0269a 10.27 * 162 109 271 4wmc0338a 6.78 * 157 114 271 4ksm0173a 12.02 * 141 97 238 37ksm0045b 2.71 ns 122 149 271 4wmc0435b 0.24 ns 139 132 271 4gwm0111 19.29 * 96 168 264 11ksm0051a 56.88 8 198 73 271 4wmc0051 74.88 8 60 203 263 12wmc0475 0.09 ns 137 134 271 4
224
Supplemental material 6.4 QTL for ACG content and composition detected on 7BS of the Sunco/Tasman doubled haploid population by
Composite Interval Mapping (CIM) after the original map was saturated with more SSR markers. A. ACG1 concentration (μg/g), B. ACG1
content (μg/grain), C. ACG2 concentration (μg/g), D. ACG2 content (μg/grain) and E. Ratio of ACG1/ACG2. Red line = LOD threshold at
Fpr<0.001.
225
Supplemental material 6.5 Protein sequences coded by genes located in the region
of rice chromosome 6 that is syntenic to the 7BS QTL for ACG traits in
Sunco/Tasman (Gramene databases accessed 19 January 2010).
BAC/PAC clones Accession Protein propertiesAP005387 Q5Z6M3 Aluminum-activated malate transporter-like
Q5Z6M4 Aluminum-activated malate transporter-likeQ5Z6M5 Aluminum-activated malate transporter-likeQ5Z6L5 Hydroxyproline-rich glycoprotein-likeQ5Z6M0 NHL repeat-containing protein-likeQ5Z6L4 Pr1-like proteinQ5Z6K4 PRLI-interacting factor G-likeQ5Z6M6 Putative nucellin-like aspartic proteaseQ5Z6K9 Putative potassium transporterQ5Z6K2 Putative flavonoid 3-O-glucosyltransferase
AP003491 Q5VQ32 Leaf senescence protein-likeQ5VQ36 Leaf senescence protein-likeQ5VQ37 Leaf senescence protein-likeQ5VQ38 Leaf senescence protein-likeQ5VQ40 Leaf senescence protein-likeQ5Z6K4 PRLI-interacting factor G-likeQ5VQ48 Putative amidaseQ5VQ44 Putative bacterial blight resistance proteinQ5Z6K2 Putative flavonoid 3-O-glucosyltransferase
AP005813 Q8H2H0 Hd1Q5VN15 Leaf senescence protein-likeQ8H2I6 Leaf senescence protein-likeQ8H2G7 Putative curly leaf proteinQ5VN12 Putative Importin 9Q8H2H2 Putative peroxidaseQ5VN06 Putative Polycomb protein EZ1Q5VN14 Putative signal peptidase 18K chainQ8H2I4 Putative signal peptidase subunitQ5VN11 Somatic embryogenesis receptor kinase 1-like
AP003044 Q5VR95 Armadillo/beta-catenin repeat protein-related-likeQ5VR96 basic/helix-loop-helix 86Q9FDX8 Hd1Q5VR92 Putative adaptor protein kanadaptinQ9FP07 Putative curly leaf proteinQ9FP22 Putative heat shock factor binding proteinQ5VN12 Putative Importin 9Q9FNZ8 Putative Na+-dependent neutral amino acid transporterQ9FP19 Putative nucleolar protein family A member 2Q9FP11 Putative Peroxidase 49Q5VN06 Putative Polycomb protein EZ1Q9FP16 Putative polyproteinQ9FP13 Putative somatic embryogenesis protein kinase 1Q5VN11 Somatic embryogenesis receptor kinase 1-like
226
Supplemental material 6.5 (continued)
BAC/PAC clones Accession Protein propertiesAP003538 Q5VPW0 Hydroxyproline-rich glycoprotein-like
Q5VPX2 Putative resistance proteinAP003540 Q5VPU9 Carboxyl-terminal peptidase-like
Q5VPU1 HGWP repeat containing protein-likeAP005822 Q5VMY9 Hydroxyproline-rich glycoprotein-like
Q5VMZ3 Hydroxyproline-rich glycoprotein-likeQ5VMZ4 Hydroxyproline-rich glycoprotein-likeQ5VMY4 Putative DNA topoisomerase IQ5VN00 Putative NBS-LRR class RGAQ5VMY6 Putative o-methyltransferaseQ5VMZ1 Splicing coactivator subunit-like proteinQ5VMZ5 Zinc knuckle containing protein-like
AP005695 Q5VMY9 Hydroxyproline-rich glycoprotein-likeQ5VN46 Putative dehydration-responsive protein RD22Q5VMY4 Putative DNA topoisomerase IQ5VMY6 Putative o-methyltransferaseQ5VMS9 Putative UDP-glycosyltransferaseQ5VMT1 Putative UDP-glycosyltransferaseQ5VN44 Putative UDP-glycosyltransferaseQ5VMZ1 Splicing coactivator subunit-like protein
AP006050 Q5VMR7 2x PHD domain containing protein-like Q5VMR0 Calcineurin B-like protein Q5VMS7 HGWP repeat containing protein-like Q5VMS6 HGWP repeat containing protein-like Q5VMR2 Hydroxyproline-rich glycoprotein-like Q5VMS2 Hydroxyproline-rich glycoprotein-like Q5VMR5 Phosphatidylinositol 3-and 4-kinase family-like Q5VMS8 Pr1-like protein Q5VMS9 Putative UDP-glycosyltransferase Q5VMT1 Putative UDP-glycosyltransferase Q5VMS1 Putative UDP-glycosyltransferase Q5VMS0 Putative UDP-glycosyltransferase Q5VMS3 UDP-glycosyltransferase-like Q5VMS5 Zinc knuckle containing protein-like Q5VMS4 Zinc knuckle containing protein-like
AP004791 Q5VNE3 BRUSHY1-like Q5VMR0 Calcineurin B-like protein Q5VNF6 Endosperm specific protein-like Q5VNF4 HAP3 transcriptional-activator Q5VMR2 Hydroxyproline-rich glycoprotein-like Q5VNE7 Methyl-CpG binding protein-like Q5VNF3 Patatin-like phospholipase domain containing protein-like Q5VNG4 Putative auxin-independent growth promoter Q5VNE4 Putative dof zinc finger protein Q5VNF2 Putative lectin-like receptor kinase Q5VNF8 Putative TMV-MP30 binding protein 2C
227
Supplemental material 6.5 (continued)
BAC/PAC clones Accession Protein propertiesAP005830 Q6YVE7 Mitochondrial aspartate-glutamate carrier protein-like
Q6YVD9 Peptidase family-like protein AP005659 Q5VN64 NBS-LRR disease resistance protein-like
Q5VMI1 Putative brassinosteroid insensitive 1 Q5VN67 Putative NBS-LRR disease resistance protein Q5VN70 Putative NBS-LRR disease resistance protein Q5VN78 Putative NBS-LRR disease resistance protein Q5VN81 Putative NBS-LRR disease resistance protein Q5VN82 Putative nitrate-induced NOI protein Q5VMI0 C -glycosyltransferase (OsCGT ) Q5VN75 Subtilase-like protein
AP006584 Q5VMG6 : Epstein-Barr virus EBNA-1-like protein Q5VMH2 : HGWP repeat containing protein-like Q5VMH1 : Pr1-like protein Q5VMH7 : Pr1-like protein Q5VMI1 : Putative brassinosteroid insensitive 1 Q5VMI0 : Putative UDP-glycosyltransferase
Q5VMG8 : Putative UTP-glucose glucosyltransferase Q5VMH3 : Zinc knuckle containing protein-like
AP006860 Q5VMD9 : Cell wall protein-like Q5Z577 : Embryogenesis transmembrane protein-like Q5Z580 : Embryogenesis transmembrane protein-like Q5Z590 : Hydroxyproline-rich glycoprotein-like Q5Z575 : Putative embryogenesis transmembrane protein Q5Z589 : Putative glucosyltransferase-3 Q5VME5 : Putative UDP-glycosyltransferase
Q5Z588 : Root cap protein 1-like Q5VMD8 : Zinc finger protein-like
AP005761 Q5Z569 Aminotransferase-like protein
Q5Z577 Embryogenesis transmembrane protein-like Q5Z580 Embryogenesis transmembrane protein-like Q5Z570 Embryogenesis transmembrane protein-like Q5Z567 Embryogenesis transmembrane protein-like Q5Z590 Hydroxyproline-rich glycoprotein-like
Q5Z575 Putative embryogenesis transmembrane protein Q5Z589 Putative glucosyltransferase-3 Q5Z588 Root cap protein 1-like
228
Supplemental material 6.6 Protein sequences coded by genes located in the region
of rice chromosome 8 that is syntenic to the 7BS QTL for ACG traits in
Sunco/Tasman (Gramene databases accessed 19 January 2010).
BAC/PAC clones Accession Protein propertiesAP005245 Q6Z3T8 Auxin-regulated protein-like
Q6Z3R2 Cyt-P450 monooxygenaseQ6Z3T7 Epstein-Barr virus EBNA-1-like proteinQ6Z3T3 Putative 60S ribosomal protein L31Q6Z3T9 Putative DNA-damage-repair/toleration proteinQ6Z3S1 Putative leucine-rich repeat/receptor protein kinaseQ6Z3R6 Putative transcription factor RAU1Q6Z3R9 RRNA methylase-like
AP005254 Q6Z3F0 Cyt-P450 monooxygenaseQ6Z3R2 Cyt-P450 monooxygenaseQ6YVS8 N-acetyltransferase and Transcription factor-like proteinQ6Z3D6 Putative Cyt-P450 monooxygenaseQ6YVT1 Putative ethylene-insensitive proteinQ6YVS9 Splicing coactivator subunit-like protein
AP005816 Q6YVT6 Circumsporozoite protein-likeQ6Z3F0 Cyt-P450 monooxygenaseQ6YVT0 Lipoxygenase, chloroplastQ7EXZ6 Lipoxygenase-like proteinQ6YVS8 N-acetyltransferase and Transcription factor-like proteinQ7EXZ4 Putative beta-glucosidase isozyme 2Q7EXZ5 Putative beta-glucosidase isozyme 2Q6YVT1 Putative ethylene-insensitive proteinQ7EXZ2 Putative SBP-domain proteinQ6YVS9 Splicing coactivator subunit-like protein
AP006049 Q84YJ6 DNA-binding protein family-likeQ7EXZ6 Lipoxygenase-like proteinQ84YK8 Probable lipoxygenase 8, chloroplast precursorQ84YJ8 Putative alcohol dehydrogenase homologQ7EXZ4 Putative beta-glucosidase isozyme 2Q7EXZ5 Putative beta-glucosidase isozyme 2Q84YK7 Putative beta-glucosidase isozyme 2Q84YK6 Putative beta-glucosidase isozyme 2 precursorQ84YJ1 Putative cup-shaped cotyledonQ7EXZ0 Putative floral organ regulatorQ84YJ9 Putative high-affinity potassium transporterQ7EXZ2 Putative SBP-domain proteinQ84YK4 Putative SBP-domain protein 5Q7EXY6 Selenium binding protein-like protein
AP004765 Q6Z8N5 3-hydroxy-3-methylglutaryl-coenzyme A reductase 3Q6Z8M4 Lectin-like protein kinase-likeQ7EZ92 Myosin heavy chain-like proteinQ6Z8N6 Protein cdc2 kinase
229
Supplemental material 6.6 (continued)
BAC/PAC clones Accession Protein properties AP004765 Q6Z8P2 Putative aminoacylase
Q6Z8N8 Putative AT-hook DNA-binding proteinQ6Z8N9 Putative AT-hook DNA-binding proteinQ6Z8M5 Putative lectin-like protein kinaseQ6Z8N3 Putative phosphoprotein phosphatase PP7Q6Z8M9 Putative proton pump interactorQ6Z8P4 Putative PSR9Q6Z8L7 Putative Rab geranylgeranyltransferase, beta subunitQ6Z8M8 Putative SPL1-Related2 proteinQ6Z8N7 Thylakoid lumen protein, chloroplast-like
AP004761 Q7EZ92 Myosin heavy chain-like proteinQ7EZ93 Putative C2H2 zinc-finger proteinQ84JI5 Putative C2H2 zinc-finger proteinQ7EZ84 Putative calcium-transporting ATPase 8, plasma membrane-typeQ84JY7 Putative calcium-transporting ATPase 8, plasma membrane-typeQ84Z61 Putative dihydroflavonol 4-reductaseQ7EZ87 Putative dihydroflavonol reductaseQ84Z70 Putative flavonol 4'-sulfotransferaseQ84Z52 TDPOZ4-likeQ7EZ88 Ternary complex factor-like
AP004708 Q84Z89 30S ribosomal protein S16-likeQ7EZA8 Myosin heavy chain-like proteinQ7EZA6 Oxidase-likeQ7EZA7 Oxidase-likeQ7EZA3 Oxysterol-binding protein-likeQ84Z91 Oxysterol-binding protein-likeQ7EZ93 Putative C2H2 zinc-finger proteinQ84JI5 Putative C2H2 zinc-finger proteinQ7EZ84 Putative calcium-transporting ATPase 8, plasma membrane-typeQ84JY7 Putative calcium-transporting ATPase 8, plasma membrane-typeQ7EZB2 Putative chitinaseQ84Z87 Putative microtubule-associated proteinQ84Z90 Putative pathogenesis-related proteinQ7EZB0 Putative serine/threonine-specific receptor protein kinase
AP004622 Q6YZW0 Auxin response factor 7bQ7EZA8 Myosin heavy chain-like proteinQ7EZA6 Oxidase-likeQ7EZA7 Oxidase-likeQ6YZW3 Pentatricopeptide (PPR) repeat-containing protein-likeQ7EZB2 Putative chitinaseQ6YZW7 Putative leucine zipper-containing proteinQ6YZW6 Putative mitochondrial energy transfer proteinQ6YZW2 Putative oligouridylate binding proteinQ6YZW8 Putative pumilio-family RNA-binding domain-containing protein
230
Supplemental material 6.6 (continued)
BAC/PAC clones Accession Protein propertiesAP004622 Q6YZW4 Putative ribosomal large subunit pseudouridine synthase C protein
Q7EZB0 Putative serine/threonine-specific receptor protein kinaseQ6ZBK6 Putative stress related-like protein interactor
AP005509 Q6YZW0 Auxin response factor 7bQ7F1K3 P53 binding protein-likeQ7F1K4 P53 binding protein-likeQ7F1K5 P53 binding protein-likeQ6YZW3 Pentatricopeptide (PPR) repeat-containing protein-likeQ6YZW7 Putative leucine zipper-containing proteinQ6YZW6 Putative mitochondrial energy transfer proteinQ6YZW2 Putative oligouridylate binding proteinQ6YZW8 Putative pumilio-family RNA-binding domain-containing proteinQ7F1K6 Putative receptor-like protein kinaseQ6YZW4 Putative ribosomal large subunit pseudouridine synthase C protein
AP003887 Q7F1J8 DnaJ protein family-likeQ7F1F1 Putative auxin-induced proteinQ6ZK18 Putative inositol 1,4,5-trisphosphate 5-phosphataseQ7F1J9 Putative L-ascorbate peroxidaseQ6ZK21 Putative signal recognition particle receptor beta subunitQ7F1J2 Putative speckle-type POZ proteinQ7F1J5 Putative speckle-type POZ proteinQ7F1J7 Putative speckle-type POZ proteinQ7F1J1 Zinc finger POZ domain protein-likeQ7F1J3 Zinc finger POZ domain protein-like
AP003888 Q84QW1 basic/helix-loop-helix 91Q7F1E6 Pentatricopeptide (PPR) repeat-containing protein-likeQ7F1F2 Putative 70 kDa peptidylprolyl isomeraseQ84QV6 Putative 70 kDa peptidylprolyl isomeraseQ7F1E7 Putative amino acid permeaseQ7F1F1 Putative auxin-induced proteinQ84QW4 Putative auxin-induced proteinQ84QV4 Putative beta-1,3-glucanaseQ84QW0 Putative GTP-binding proteinQ84QW3 Putative ribosomal protein L32Q84QV1 Putative type 1 capsule synthesis geneQ84QV2 Receptor-like protein kinase-like
231
Supplemental material 6.7 Synteny of Sunco/Tasman doubled haploid chromosome 4B region harbouring minor QTL for total ACG1 and ACG2
content with the physical maps of Chinese Spring wheat and rice chromosome 3.
232
Supplemental material 6.8 Wheat 3B sequences that show interrupted synteny of wheat 7BS and rice 6 (Gramene, access 27 April 2012).
Start StopTa.21873TC254600TA81015_4565 6,019,836.00 bp
LOC_Os06g06260 GDSL-like lipase/acylhydrolaseLOC_Os06g06270.1 Transcription elongation factor Elf1 like LOC_Os06g25880 retrotransposon proteinLOC_Os06g25890 retrotransposon protein
BF475065-3B pae2008a-3B-284 111,662,487.00 bp Ta.13866 7,497,601.00 bp 7,497,687.00 bp LOC_Os06g13580 expressed protein, unidentifiedTA75771_4565PUT-153a-Triticum_aestivum-20991TC265741Ta.10074 17,539,154.00 bpPUT-153a-Triticum_aestivum-20993 LOC_Os06g29450 expressed protein, unidentifiedTA96955_4565 LOC_Os06g29460 expressed protein, unidentified
23,674,818.00 bp
98,898,079.00 bp
673,967,555bp
445,912,012.00 bp
Gene functionLocationwheat 3B EST Wheat Accession Rice 6 marker from physical map Gene locusPosition
LOC_Os06g30370 osMFT1 MFT-Like1 homologous to Mother of FT and TFL1 gene; contains Pfam profile PF01161: Phosphatidylethanolamine-binding
cyclinLOC_Os06g114106,019,913.00 bp
17,539,356.00 bp
BG263580-3B pae2008a-3B-1857 16,876,437.00 bp 16,876,514.00 bp
17,539,142.00 bpBJ233340-3B pae2008a-3B-1153
15,133,732.00 bp 15,133,764.00 bpPUT-157a-Zea_mays-025599pae2008a-3B-260AW506610-3B
BF482491 dvo2010a-3D-BF482491 PUT-153a-Triticum_aestivum-28532 2,898,072.00 bp 2,898,614.00 bp
BE442681 dvo2010a-6D-BE442681 6,019,439.00 bp
28,369,221.00 bp
233
Supplemental material 6.8 (continue)
Start StopLOC_Os06g13640 expressed protein, unidentifiedLOC_Os06g13650 alpha-mannosidase 2LOC_Os06g13660 alanyl-tRNA synthetaseLOC_Os06g13670 E2F family transcription factorLOC_Os06g13680 B12D proteinLOC_Os06g13690 hypothetical protein, unknownLOC_Os06g13700 hypothetical protein, unknownLOC_Os06g13710 glycosyltransferaseLOC_Os06g13720 dehydrogenase E1 component domain containing proteinLOC_Os06g13730 glutamate receptor precursorLOC_Os06g13740 transposon proteinLOC_Os06g13750 expressed protein, unidentifiedLOC_Os06g13760 glycosyl transferase 8 domain containing proteinLOC_Os06g13770 transposon proteinLOC_Os06g13780 expressed protein, unidentifiedLOC_Os06g13789 hypothetical protein, unknownLOC_Os06g13800 conserved hypothetical proteinLOC_Os06g13810 pyrophosphate--fructose 6-phosphate 1-
phosphotransferase subunit betaLOC_Os06g13820 dynaminLOC_Os06g13830 endoglucanaseLOC_Os06g13839 RNA recognition motif containing proteinLOC_Os06g13850 OsFBX193 - F-box domain containing proteinLOC_Os06g13860 RCD1LOC_Os06g13870 U-box protein CMPG1LOC_Os06g13880 expressed protein, unidentifiedLOC_Os06g13890 conserved hypothetical proteinLOC_Os06g13900 transposon protein
LOC_Os06g13910 hypothetical protein, unknown
wheat 3B EST Wheat Accession Position Rice 6 marker from physical map Location Gene locus
729,556,473.00 bp TA86527_4565 PUT-153a-Triticum_aestivum-16512 TC238943
7,550,588.00 bp 7,748,466.00 bp
Gene function
BF485490-3B pae2008a-3B-2083
234
Supplemental material 6.9 Synteny between 7BS of wheat and Brachypodium distachyon at BRADIG43410 locus (115bp) (red box). Genome
Browser for 7BS_Syn_Build_0.1:577734..597734 was taken from www.wheatgenome.info/.
235
Supplemental material 6.10 Synteny block between Brachypodium distachyon
chromosome 1 and rice chromosomes 6 and 10. Illustration was taken from Gramene
database (accessed 11 March 2012). Blocks in blue colour are synteny block between
rice chromosme 6 and the Brachypodium chromsome 1, while the large white
chromosome is the Brachypodium distachyon chromosome 1. Small red rectangle in the
Brachypodium distachyon chromosome shows the location of syntenic SNP marker
BE352570.
236
Supplemental material 6.11 Synteny block between Brachypodium distachyon
chromosome 3 and rice chromosomes 8 and 10. Illustration was taken from Gramene
database (accessed 11 March 2012). Blocks in blue colour are synteny block between
rice chromosme 8 and Brachpodium chromosome 3, while the large white chromosome
is the Brachypodium distachyon chromosome 3. Small red rectangle in the
Brachypodium distachyon chromosome shows the location of sythenic SNP marker
BE445287.
237
Supplemental material 6.12 Multiple alignments of the UDP-glycosyltransferases
from the region of rice chromosome 6 than is syntenic with the Ratio QTL on 7BS of
Sunco/Tasman with other UDP-glycosyltransferases. The sequences are similar to that
shown in Figure 14. Secondary structure conservation shown by pink (-helix) and
yellow (-helix) shades. The red arrows shows His-33 and Asp-163 residues that are
catalytically important for interaction with UDP-sugar, while the blue arrow shows the
single amino acid polymorphism between the putative O-glycosyltransferases and C-
glycosyltransferases. The alignment is available on the next page.
238
239
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